Value Stream Mapping: A Method That Makes the Waste in the Process Visible

*Nuri Ozgur Dogan and Burcu Simsek Yagli*

### **Abstract**

Defining customer and value in lean thinking is crucial. All wastes that do not add value to the customer in business processes should be eliminated. In the real world and related literature, there are various methods used to eliminate waste and improve processes. One of the methods frequently used is the value stream mapping (VSM). VSM is preferred since it enables to take the picture of a process. Moreover, VSM is the identification of all activities that create and/or do not create value in the processes, from the supplier of the product or service to the customer. This chapter deals with lean philosophy, lean techniques and specifically the VSM method. In addition, some examples of VSM applications in the service and production sectors are discussed and the findings obtained from these applications are evaluated. Finally, the chapter concludes with some managerial implications as well as potential future research areas.

**Keywords:** lean thinking, lean techniques, production and service sector, value stream mapping, waste

### **1. Introduction**

Originating from Toyota production system (TPS), lean production (LP) or lean manufacturing (LM) has now become a well-known and widely adopted philosophy all over the world. Its first usages were limited with the production industry and therefore its initial applications emerged in the manufacturing businesses. As time passes, the service industry has begun to utilize from the LP philosophy and/ or techniques. As the adaptation of lean expanded from production sector to service sector, its concept transformed from LP to lean thinking (LT).

Historical evolution of the "lean" started with TPS and continued as LP/LM, and finally became LT. No matter what anyone says, each of these terms indicates the same concept. Eliminating or at least minimizing the waste (Japanese: muda) in a system is the basic philosophy of lean and to produce the maximum output by using minimum resources is the main goal of it. Lean seeks for a system that tries to detract non-value added things from the processes and bring the value-added things into the forefront. These efforts become meaningful if the value is defined correctly and the system is designed and conducted truly. Value must be defined by the customer since he/she is the end user of the product and/or service. Thus, to give exactly what the customer wants, businesses must take into consideration the concepts of efficiency and quality. It is clear that an efficient and quality focused system uses the resources exactly as needed and produces products and/or services that satisfy the customers.

Many organizations from production or service sectors implement lean production as its main system or apply lean principles partially in its specific activities. These organizations utilize from LT with the aims of becoming more efficient, more competitive, and more quality oriented. Furthermore, in recent years LT spread from a single business to supply chains of multiple businesses. It is possible to say that LT attracts many businesses and these businesses want to transform into a lean business. Lean transformation process is an important inflection point for a business and it must be carefully initiated, designed and managed. The starting point of this transformation process is crucial and right method(s) must be used during the phase. Value stream mapping (VSM), one of the methods of LT, is the most suitable method that can be used in the first step. VSM is a paper and pencil based method that focuses on the current state of a process, makes all value and non-value added activities visible, and proposes a lean future state. VSM is dealt with in this chapter in a detailed way.

The rest of the chapter is organized as follows. Section 2 focuses on lean philosophy. Lean techniques are examined in Section 3, and VSM is explained in Section 4. In Section 5, there are VSM examples from the service and production sector for a better understanding of the subject. Finally, this chapter ends with discussion and conclusion.

### **2. Lean philosophy**

Businesses should be recognized the importance of customer and value concepts. Customers do not want features that do not create value in products or services. All sectors, both product and service sector, should pay attention to this situation in order to compete with their competitors. This is because customers are not willing to pay extra for features that do not create value. Value can be categorized into three types: value added, non-value added and necessary non-value added operations [1]. Value added operations are processes that please the customer and must be in the process. Necessary non-value added operations are wasteful but necessary. Lastly, non-value added operations are completely wasteful and must be eliminated.

Lean philosophy is defined by Radnor et al. [2] as *"Lean as a management practice based on the philosophy of continuously improving processes by either increasing customer value or reducing non-value adding activities (muda), process variation (mura), and poor work conditions (muri)."* As can be seen from the definition, lean philosophy has emerged within the framework of some elements, especially waste (muda). Lean production is typically believed to be 7 types of waste [3]. These wastes are over production, waiting, transportation, over processing, inventory, unnecessary motions and defects (**Figure 1**).

The importance given to the service sector is increasing day by day. The lean production mentality continues to be implemented in the service sector. Lean philosophy, both production and service sector value, optimization, quality, standardization and simplification principles are common [4]. However, the wastes defined as 7 types in lean production are 10 types (**Figure 2**) in the service sector [5].

If the wastes are eliminated and the costs of waiting in stock are reduced, customer satisfaction and related sales will increase. Therefore, the purpose of both customers, employees and business partners will be achieved through the adoption of lean philosophy. On the other hand, in order to ensure continuous improvement, the wastes in the process must be converted to value. Furthermore, due to the rapid change in customer expectations, it is important to achieve perfection. Thus, Womack and Jones [6] proposed a *The 5 Steps Model* to help transform from value to perfection [7]. **Table 1** contains the 5 steps model and explanations of the expressions [6–11].

**41**

**Figure 2.**

*Ten types of waste (service sector).*

**Figure 1.**

*Seven types of waste.*

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

A number of lean methods are used in the realization of these steps (detailed descriptions in the next section). JIT and Kaizen, in particular, are the main philosophies in achieving continuous improvement and in reaching perfection [12]. Besides, lean philosophy has many benefits for businesses, employees and customers. These benefits are, reduced lead time, less rework, financial savings, increased process understanding, reduced inventory, less process waste, satisfied customer,

There are some principles to apply the lean philosophy successfully in a organization [14]. It is a pyramid with 4P of lean way formed by the Liker's 4P of the Toyota way [15]. The 14 principles are represented by 4P [16]: philosophy, process,

standardized processes, improved knowledge management [3, 13].

people and partner, problem solving (**Figure 3**).

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible DOI: http://dx.doi.org/10.5772/intechopen.83798*

*Lean Manufacturing and Six Sigma - Behind the Mask*

in a detailed way.

**2. Lean philosophy**

motions and defects (**Figure 1**).

conclusion.

Many organizations from production or service sectors implement lean production as its main system or apply lean principles partially in its specific activities. These organizations utilize from LT with the aims of becoming more efficient, more competitive, and more quality oriented. Furthermore, in recent years LT spread from a single business to supply chains of multiple businesses. It is possible to say that LT attracts many businesses and these businesses want to transform into a lean business. Lean transformation process is an important inflection point for a business and it must be carefully initiated, designed and managed. The starting point of this transformation process is crucial and right method(s) must be used during the phase. Value stream mapping (VSM), one of the methods of LT, is the most suitable method that can be used in the first step. VSM is a paper and pencil based method that focuses on the current state of a process, makes all value and non-value added activities visible, and proposes a lean future state. VSM is dealt with in this chapter

The rest of the chapter is organized as follows. Section 2 focuses on lean philosophy. Lean techniques are examined in Section 3, and VSM is explained in Section 4. In Section 5, there are VSM examples from the service and production sector for a better understanding of the subject. Finally, this chapter ends with discussion and

Businesses should be recognized the importance of customer and value concepts. Customers do not want features that do not create value in products or services. All sectors, both product and service sector, should pay attention to this situation in order to compete with their competitors. This is because customers are not willing to pay extra for features that do not create value. Value can be categorized into three types: value added, non-value added and necessary non-value added operations [1]. Value added operations are processes that please the customer and must be in the process. Necessary non-value added operations are wasteful but necessary. Lastly, non-value added operations are completely wasteful and must be eliminated.

Lean philosophy is defined by Radnor et al. [2] as *"Lean as a management practice based on the philosophy of continuously improving processes by either increasing customer value or reducing non-value adding activities (muda), process variation (mura), and poor work conditions (muri)."* As can be seen from the definition, lean philosophy has emerged within the framework of some elements, especially waste (muda). Lean production is typically believed to be 7 types of waste [3]. These wastes are over production, waiting, transportation, over processing, inventory, unnecessary

The importance given to the service sector is increasing day by day. The lean production mentality continues to be implemented in the service sector. Lean philosophy, both production and service sector value, optimization, quality, standardization and simplification principles are common [4]. However, the wastes defined as 7 types in lean production are 10 types (**Figure 2**) in the service sector [5]. If the wastes are eliminated and the costs of waiting in stock are reduced, customer satisfaction and related sales will increase. Therefore, the purpose of both customers, employees and business partners will be achieved through the adoption of lean philosophy. On the other hand, in order to ensure continuous improvement, the wastes in the process must be converted to value. Furthermore, due to the rapid change in customer expectations, it is important to achieve perfection. Thus, Womack and Jones [6] proposed a *The 5 Steps Model* to help transform from value to perfection [7]. **Table 1** contains the 5 steps model and explanations of the expressions [6–11].

**40**

A number of lean methods are used in the realization of these steps (detailed descriptions in the next section). JIT and Kaizen, in particular, are the main philosophies in achieving continuous improvement and in reaching perfection [12]. Besides, lean philosophy has many benefits for businesses, employees and customers. These benefits are, reduced lead time, less rework, financial savings, increased process understanding, reduced inventory, less process waste, satisfied customer, standardized processes, improved knowledge management [3, 13].

There are some principles to apply the lean philosophy successfully in a organization [14]. It is a pyramid with 4P of lean way formed by the Liker's 4P of the Toyota way [15]. The 14 principles are represented by 4P [16]: philosophy, process, people and partner, problem solving (**Figure 3**).


*The 5 steps model.*

Koskela [17] also defined the principles (11 principles) adopted in lean thinking as Liker [10]. The main theme of the lean principles proposed by the two authors is similar to that of Womack and Jones [6] in the 5-step model. This theme consists of defining the value, providing the flow, solving problems with lean techniques and aiming to reach perfection.

### **3. Lean techniques**

Within the scope of lean thinking, there are numerous methods used to reach the targets and minimize the wastes. Some of the lean methods for becoming lean as a system are crucial in the lean systems such as value stream mapping (VSM),

**43**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

single minute exchange of dies (SMED), the 5S system, one piece flow, just in time (JIT), pull system (Kanban), Poka-Yoke, total productive maintenance, Kaizen, visual controls/management, 5 whys (5N), standardized work, spaghetti diagram, DMAIC, PDCA and so on [12] and they will be briefly described in this section.

SMED method is developed by Shingo in the 1950s and later perfected by Toyota over the years [18]. SMED has become the best practice to simplify and reduce the time spent on set up. Time is very important in lean systems and is not expected to be wasted. That's why, this method has an important place in lean techniques. Thanks to SMED method, changeover time is reduced from hours to minutes. In simple terms, it is attempted to decrease the preparation time on a machine or any process to less than 10 minutes [12]. Perhaps the best example of the application of this method is automobile racings.

Set up times is separated as internal and external. The activities performed by stopping the machine are called the internal set up time, while the activities carried out around the machine without stopping the activity are called external set up time [19]. In this point, some of the internal tasks may need to be converted to external tasks without stopping the machine [20]. Thus, continuous flow can be achieved and processes become faster and more efficient. With the improvements in internal set up time, labor savings are achieved and the downtimes of the machine decrease. Moreover, improvements to external set up times do not have a direct impact on stopping time, but may give operators the freedom to take time for other activities.

The 5S system is a visual communication technique that enables the working area to be well organized [11]. It also helps to reduce waste in the working area through general cleaning. This method is preferred when it is aimed to ensure cleanliness and organized workplace layout, to improve processes, to ensure transparency and to rise up employee satisfaction. Five Japanese words, starting with the letter *S*, are used to create this method. These words are *seiri-sort*, *seiton-straighten*, *seiso-shine*, *seiketsu-standardize* and *shitsuke-sustain* [13]. Buesa [21] stated that some experts add two new terms are safety and security. Lastly, with the implementation of the 5S cycle, it is possible to change the working environment with low costs. Moreover, employees respect to their

organizations and themselves, and inventory and material costs are decreased.

[12]. This can be achieved by reducing the lot size in lean production.

By the one-piece flow technique, it is intended to move a single piece at a time between operations. The one-piece flow method takes into account factors such as sorting jobs, calculating installation time, and determining job shop production policy [19]. Therefore, these factors need to be examined during production planning. Planning a production according to one-piece flow is an important component of lean production strategy. The installation time, the stock levels and the delivery time are directly affected by the lot size. In view of these situations, it is very important to be an agile business to respond to customer needs without creating inventory

The just in time philosophy adopted by Toyota is a system that regulates the stock level and optimizes the flow of materials. According to the JIT production strategy,

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

**3.1 Single minute exchange of dies (SMED)**

**3.2 The 5S system**

**3.3 One piece flow**

**3.4 Just in time (JIT)**

single minute exchange of dies (SMED), the 5S system, one piece flow, just in time (JIT), pull system (Kanban), Poka-Yoke, total productive maintenance, Kaizen, visual controls/management, 5 whys (5N), standardized work, spaghetti diagram, DMAIC, PDCA and so on [12] and they will be briefly described in this section.

### **3.1 Single minute exchange of dies (SMED)**

SMED method is developed by Shingo in the 1950s and later perfected by Toyota over the years [18]. SMED has become the best practice to simplify and reduce the time spent on set up. Time is very important in lean systems and is not expected to be wasted. That's why, this method has an important place in lean techniques. Thanks to SMED method, changeover time is reduced from hours to minutes. In simple terms, it is attempted to decrease the preparation time on a machine or any process to less than 10 minutes [12]. Perhaps the best example of the application of this method is automobile racings.

Set up times is separated as internal and external. The activities performed by stopping the machine are called the internal set up time, while the activities carried out around the machine without stopping the activity are called external set up time [19]. In this point, some of the internal tasks may need to be converted to external tasks without stopping the machine [20]. Thus, continuous flow can be achieved and processes become faster and more efficient. With the improvements in internal set up time, labor savings are achieved and the downtimes of the machine decrease. Moreover, improvements to external set up times do not have a direct impact on stopping time, but may give operators the freedom to take time for other activities.

### **3.2 The 5S system**

*Lean Manufacturing and Six Sigma - Behind the Mask*

flow, not just one process

inventory are prevented by JIT applications

1. Value Value is the source of the pleasure and needs of the customers who buy the product or

3. Flow Continuous flow can be achieved by detecting and eliminating the wastes in the process.

4. Pull The pull system means that production or service will not be commenced without a

5. Perfection Perfection is the last step that separates value and waste. This step regulates the flow,

service. It is the starting point of lean philosophy. It is necessary to understand the needs of the customers, to define the value correctly, and to implement this in all processes

The value stream is all the activities needed during the generating of the product or service. These activities may be activities that add or do not add value to the product or service. Additionally, with all activities being seen, wastes that non-value adding will be recognized

Furthermore, it is necessary to implement this throughout the value chain to ensure full

customer approval. This is the exact opposite of the push system. Production will be tailored to the customer in this system. In addition, over production and unnecessary

ensures the continuity of the flow and initiates the pull system. Perfection is maintained by continuous improvement. Perfection means that lean thinking is adopted and implemented

**The steps Explanations**

2. Value stream

**Table 1.** *The 5 steps model.*

**42**

**Figure 3.**

*The 4P of the lean way [10].*

aiming to reach perfection.

**3. Lean techniques**

Koskela [17] also defined the principles (11 principles) adopted in lean thinking as Liker [10]. The main theme of the lean principles proposed by the two authors is similar to that of Womack and Jones [6] in the 5-step model. This theme consists of defining the value, providing the flow, solving problems with lean techniques and

Within the scope of lean thinking, there are numerous methods used to reach the targets and minimize the wastes. Some of the lean methods for becoming lean as a system are crucial in the lean systems such as value stream mapping (VSM),

The 5S system is a visual communication technique that enables the working area to be well organized [11]. It also helps to reduce waste in the working area through general cleaning. This method is preferred when it is aimed to ensure cleanliness and organized workplace layout, to improve processes, to ensure transparency and to rise up employee satisfaction. Five Japanese words, starting with the letter *S*, are used to create this method. These words are *seiri-sort*, *seiton-straighten*, *seiso-shine*, *seiketsu-standardize* and *shitsuke-sustain* [13]. Buesa [21] stated that some experts add two new terms are safety and security. Lastly, with the implementation of the 5S cycle, it is possible to change the working environment with low costs. Moreover, employees respect to their organizations and themselves, and inventory and material costs are decreased.

### **3.3 One piece flow**

By the one-piece flow technique, it is intended to move a single piece at a time between operations. The one-piece flow method takes into account factors such as sorting jobs, calculating installation time, and determining job shop production policy [19]. Therefore, these factors need to be examined during production planning. Planning a production according to one-piece flow is an important component of lean production strategy. The installation time, the stock levels and the delivery time are directly affected by the lot size. In view of these situations, it is very important to be an agile business to respond to customer needs without creating inventory [12]. This can be achieved by reducing the lot size in lean production.

### **3.4 Just in time (JIT)**

The just in time philosophy adopted by Toyota is a system that regulates the stock level and optimizes the flow of materials. According to the JIT production strategy,

what is needed is produced in the desired amount and time [22]. In this concept, the production of more than the amount needed and stocking are considered as waste. Thus, wastes in processes are eliminated by using the JIT philosophy. Furthermore, the quality-related problems are easily identified thanks to the low level of inventory. In addition to these advantages, JIT offers businesses the flexibility and speed required to keep up with global competition.

### **3.5 Pull system/Kanban**

In lean thinking, workflows are usually applied with the pull system. The pull system is defined as the system by which the customer decides to start production or service [23]. In this system, since the production is started when there is demand, the wastes like excess inventory and overproduction is prevented. In addition, the companies that decide to implement the pull system must fulfill their customer demands within a certain time frame. For this purpose, it is inevitable to use *Kanban* cards. Kanban cards is a Japanese term given to cards used to control the flow in the process such as inventory control [19]. Additionally, control of the variations in demand and production can be provided with Kanban cards [24].

### **3.6 Poka-Yoke**

A Japanese word, Poka-Yoke, means mistake proofing and error avoidance [25]. In this way, errors are detected at the source and prevented from passing to the next step. The basic principle of the technique is to reduce the cost by reducing the number of defective parts that can occur during the production process to zero [26]. Poka-Yoke is preferred for quality at the source. Moreover, the Andon technique, which consists of lights that make it appear when errors occur, are also used.

### **3.7 Total productive maintenance**

Lean systems attach importance to continuous flows. The businesses want to avoid as much as possible the failures and machine errors that may occur during the process. For this reason, total productive maintenance (TPM) technique, should be implemented as routine preventive maintenance with the participation of all employees. TPM is an approach that requires the participation of all the employees within the daily production activities, which also brings the necessity of the maintenance of the equipment that it works on, prevents the errors and maximizes the efficiency of the equipment [27]. However, it is necessary to provide interdepartmental trainings to employees for this maintenance.

#### **3.8 Kaizen**

The main philosophy of lean system is the adoption of continuous flow and improvement. All other lean methods try to achieve this philosophy to perfection [28]. Kaizen, based on the concept of continuity, is a process improvement program that will never end. In order to make improvements in the existing production system and to find solutions to the problems identified, employees from different disciplines must come together in the Kaizen activities. In this meeting, wastes are defined and attempts are made to prevent the occurrence of other wastes. Lastly, the main basis of continuous improvement is undoubtedly the fact that top management believes the lean philosophy and provides full support to employees.

**45**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

root of the problem is determined and solved not to occur again.

The spaghetti diagram is the visualization of the movement and transportation of the product or service in the value stream [29]. Employees can collect the data via this method [13]. Because the movements of products and services are clearly visible with this activity. Thus, the wastes during the flow can be easily determined. Besides, the problem determination and solution suggestions for eliminating non value added work steps and distances can be collected with the help of the opinions

The 5N method is briefly the process of defining and writing specific problems. As it is understood from this definition, it is questioned why the problems arise and their answers are written under the determined problem. If the answer is not the root cause of the problem [13, 30], the evaluators will continue to ask until the root cause is determined. In the 5N method, it is tried to eliminate the wastes by asking the questions of the cause and the reason causing this problem [31]. In this way, the

The standardization of works and processes has been developed based on the kaizen philosophy [32]. In order to ensure continuous flow, it is necessary to repeat the processes with the same quality every time. By using the standardized work method for repetitive tasks, employees will be trained in the steps of the processes according to the predetermined standards, which will allow quality improvement. Moreover, as employees know exactly what to do, their work satisfaction and

Visual control is a method based on organizing the working area so that management and workers can understand whether there is something going wrong in a way. The use of visual control method wherever the process takes place and its adoption can be evaluated as visual management. By using simple visual schemes, the communication between the employees becomes clear and the areas of responsibility of the employees can be determined by ground lines. In this way, processes can be viewed visually, employees are not forced and errors are

DMAIC and PDCA are cycles that monitor and examine business processes from start to finish. DMAIC (define-measure-analyze-improve-control) is an integral part of the six sigma method. This method is a systematic and result oriented. If there is flexibility during the processes, the most effective results can be obtained from this method. In addition, steps that do not add value are eliminated [33].

The PDCA (plan-do-check-act) cycle was first developed by Shewhart [12]. This method is more effective than the philosophy of doing it right the first time. Because, by using the PDCA cycle, better improvement methods are sought [33]. PDCA cycle consist of for stages: planning for improvement, doing improvement actions, checking the implications of improvement actions, and making effective permanent actions

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

**3.9 Spaghetti diagram**

of the employees.

**3.10 Whys (5N)**

**3.11 Standardized work**

motivation increase.

prevented.

**3.12 Visual controls/management**

**3.13 DMAIC and PDCA cycle**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible DOI: http://dx.doi.org/10.5772/intechopen.83798*

### **3.9 Spaghetti diagram**

*Lean Manufacturing and Six Sigma - Behind the Mask*

required to keep up with global competition.

**3.5 Pull system/Kanban**

Kanban cards [24].

**3.7 Total productive maintenance**

mental trainings to employees for this maintenance.

**3.6 Poka-Yoke**

what is needed is produced in the desired amount and time [22]. In this concept, the production of more than the amount needed and stocking are considered as waste. Thus, wastes in processes are eliminated by using the JIT philosophy. Furthermore, the quality-related problems are easily identified thanks to the low level of inventory. In addition to these advantages, JIT offers businesses the flexibility and speed

In lean thinking, workflows are usually applied with the pull system. The pull system is defined as the system by which the customer decides to start production or service [23]. In this system, since the production is started when there is demand, the wastes like excess inventory and overproduction is prevented. In addition, the companies that decide to implement the pull system must fulfill their customer demands within a certain time frame. For this purpose, it is inevitable to use *Kanban* cards. Kanban cards is a Japanese term given to cards used to control the flow in the process such as inventory control [19]. Additionally, control of the variations in demand and production can be provided with

A Japanese word, Poka-Yoke, means mistake proofing and error avoidance [25]. In this way, errors are detected at the source and prevented from passing to the next step. The basic principle of the technique is to reduce the cost by reducing the number of defective parts that can occur during the production process to zero [26]. Poka-Yoke is preferred for quality at the source. Moreover, the Andon technique, which consists of lights that make it appear when errors occur, are also used.

Lean systems attach importance to continuous flows. The businesses want to avoid as much as possible the failures and machine errors that may occur during the process. For this reason, total productive maintenance (TPM) technique, should be implemented as routine preventive maintenance with the participation of all employees. TPM is an approach that requires the participation of all the employees within the daily production activities, which also brings the necessity of the maintenance of the equipment that it works on, prevents the errors and maximizes the efficiency of the equipment [27]. However, it is necessary to provide interdepart-

The main philosophy of lean system is the adoption of continuous flow and improvement. All other lean methods try to achieve this philosophy to perfection [28]. Kaizen, based on the concept of continuity, is a process improvement program that will never end. In order to make improvements in the existing production system and to find solutions to the problems identified, employees from different disciplines must come together in the Kaizen activities. In this meeting, wastes are defined and attempts are made to prevent the occurrence of other wastes. Lastly, the main basis of continuous improvement is undoubtedly the fact that top management believes the lean philosophy and provides full sup-

**44**

port to employees.

**3.8 Kaizen**

The spaghetti diagram is the visualization of the movement and transportation of the product or service in the value stream [29]. Employees can collect the data via this method [13]. Because the movements of products and services are clearly visible with this activity. Thus, the wastes during the flow can be easily determined. Besides, the problem determination and solution suggestions for eliminating non value added work steps and distances can be collected with the help of the opinions of the employees.

### **3.10 Whys (5N)**

The 5N method is briefly the process of defining and writing specific problems. As it is understood from this definition, it is questioned why the problems arise and their answers are written under the determined problem. If the answer is not the root cause of the problem [13, 30], the evaluators will continue to ask until the root cause is determined. In the 5N method, it is tried to eliminate the wastes by asking the questions of the cause and the reason causing this problem [31]. In this way, the root of the problem is determined and solved not to occur again.

### **3.11 Standardized work**

The standardization of works and processes has been developed based on the kaizen philosophy [32]. In order to ensure continuous flow, it is necessary to repeat the processes with the same quality every time. By using the standardized work method for repetitive tasks, employees will be trained in the steps of the processes according to the predetermined standards, which will allow quality improvement. Moreover, as employees know exactly what to do, their work satisfaction and motivation increase.

### **3.12 Visual controls/management**

Visual control is a method based on organizing the working area so that management and workers can understand whether there is something going wrong in a way. The use of visual control method wherever the process takes place and its adoption can be evaluated as visual management. By using simple visual schemes, the communication between the employees becomes clear and the areas of responsibility of the employees can be determined by ground lines. In this way, processes can be viewed visually, employees are not forced and errors are prevented.

### **3.13 DMAIC and PDCA cycle**

DMAIC and PDCA are cycles that monitor and examine business processes from start to finish. DMAIC (define-measure-analyze-improve-control) is an integral part of the six sigma method. This method is a systematic and result oriented. If there is flexibility during the processes, the most effective results can be obtained from this method. In addition, steps that do not add value are eliminated [33].

The PDCA (plan-do-check-act) cycle was first developed by Shewhart [12]. This method is more effective than the philosophy of doing it right the first time. Because, by using the PDCA cycle, better improvement methods are sought [33]. PDCA cycle consist of for stages: planning for improvement, doing improvement actions, checking the implications of improvement actions, and making effective permanent actions


#### **Table 2.**

*Lean tools and methods and their classifications [35].*

toward improvement. In these methods, precise measurements of product and process variability are made. In addition, all processes focus on statistical control [34].

Thanks to these lean tools and methods, to adopt the lean philosophy becomes easier; at the same time the philosophy is ensured to become permanent. These techniques are also thought to eliminate waste in production and service processes. Moreover, the lean methods are divided into three categories by Radnor et al. [2] as assessment, improvement and monitoring. In addition, these methods that frequently preferred in the literature are classified by Costa and Filho [35] the frame of three categories (**Table 2**).

VSM is the most important and most widely used method. In addition, since VSM forms the main framework of this chapter, it is examined in more detail in the next section.

#### **4. Value stream mapping**

As a result of increasing interest in lean thinking, executives strive to transform their processes into a lean system. Lean techniques help ensure the lean in processes. One of the commonly applied lean methods is the value stream mapping (VSM) method introduced by Rother and Shook [36].

VSM is a demonstration of whole activities that value added and non-value added in processes by using a pen and paper [36]. VSM; a technique that helps determine and understand the resource and information flow of a product or service throughout the process. It is desirable to eliminate the wastes in the value stream in this method [29].

The aim of the method is to identify activities that non-value added to the product or service in the eyes of the customer and to improve the process by eliminating the wastes. The steps of the VSM method created to accomplish this aim are shown in **Figure 4** [36–38]:

The first step in VSM is the selection of product family with common features or similar processes to avoid complexity. Then, the current state map showing the current process is drawn. What is important here is that the entire process from supplier to customer is included in the map. In the third step, the situations necessary for the development of the process that is dealt with the future state map are mapped. The color of the third step is different because VSM has no meaning if improvements are not recommended after the current state map [36]. In the last

**47**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

step, based on the elements identified on the map, it is discussed and applied what needs to be done, how much time is needed, who should take responsibility in each

Standard symbols are accepted for demonstrating material flow, information flow and general information in VSM [23]. Some icons representing these symbols

• procure the identification of the resources causing waste during the process.

• includes different application steps and implementation plan for continuous

In addition, VSM method determines the system's takt time, lead time and cycle times. In this way, the result of improvements in the future state map can be

• *Takt time* is the speed at which goods or services must be produced to meet customer demand. Takt time is calculated by dividing the daily total production

• ensures that the examined process is handled from beginning to end

• shows the relationship between information flow and material flow

The use of the VSM method has several advantages. Advantages of VSM method

field and what the expected outcome from each activity is.

• provides visuality thanks to symbolic representation

revealed. The terms here are briefly defined (see [19, 40]):

time by daily customer demand.

are provided in **Figure 5**.

*The value stream mapping process.*

**Figure 4.**

are listed below [18, 39]:

improvement

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible DOI: http://dx.doi.org/10.5772/intechopen.83798*

#### **Figure 4.**

*Lean Manufacturing and Six Sigma - Behind the Mask*

**Classification Lean tools & methods**

Monitoring Visual control

*Lean tools and methods and their classifications [35].*

toward improvement. In these methods, precise measurements of product and process variability are made. In addition, all processes focus on statistical

Thanks to these lean tools and methods, to adopt the lean philosophy becomes easier; at the same time the philosophy is ensured to become permanent. These techniques are also thought to eliminate waste in production and service processes. Moreover, the lean methods are divided into three categories by Radnor et al. [2] as assessment, improvement and monitoring. In addition, these methods that frequently preferred in the literature are classified by Costa and Filho [35] the frame of

Assessment Value stream mapping, 5 Whys (5N), A3, Ishikawa

Improvement 5S's, spaghetti diagram, continuous flow, Kaizen,

Assessment/improvement/monitoring DMAIC (define-measure-analyze-improve-control),

standardized work

PDCA (plan-do-check-action)

diagram, process mapping, Gemba walking

pull system/Kanban, one-piece-flow, Poka-yoke, team approach to problem solving, workload balancing, Andon, Jidoka, process redesign, Heijunka, physical work setting redesign,

VSM is the most important and most widely used method. In addition, since VSM forms the main framework of this chapter, it is examined in more detail in the

As a result of increasing interest in lean thinking, executives strive to transform their processes into a lean system. Lean techniques help ensure the lean in processes. One of the commonly applied lean methods is the value stream mapping (VSM)

VSM is a demonstration of whole activities that value added and non-value added in processes by using a pen and paper [36]. VSM; a technique that helps determine and understand the resource and information flow of a product or service throughout the process. It is desirable to eliminate the wastes in the value

The aim of the method is to identify activities that non-value added to the product or service in the eyes of the customer and to improve the process by eliminating the wastes. The steps of the VSM method created to accomplish this aim are shown

The first step in VSM is the selection of product family with common features or similar processes to avoid complexity. Then, the current state map showing the current process is drawn. What is important here is that the entire process from supplier to customer is included in the map. In the third step, the situations necessary for the development of the process that is dealt with the future state map are mapped. The color of the third step is different because VSM has no meaning if improvements are not recommended after the current state map [36]. In the last

**46**

control [34].

**Table 2.**

next section.

three categories (**Table 2**).

**4. Value stream mapping**

stream in this method [29].

in **Figure 4** [36–38]:

method introduced by Rother and Shook [36].

*The value stream mapping process.*

step, based on the elements identified on the map, it is discussed and applied what needs to be done, how much time is needed, who should take responsibility in each field and what the expected outcome from each activity is.

Standard symbols are accepted for demonstrating material flow, information flow and general information in VSM [23]. Some icons representing these symbols are provided in **Figure 5**.

The use of the VSM method has several advantages. Advantages of VSM method are listed below [18, 39]:


In addition, VSM method determines the system's takt time, lead time and cycle times. In this way, the result of improvements in the future state map can be revealed. The terms here are briefly defined (see [19, 40]):

• *Takt time* is the speed at which goods or services must be produced to meet customer demand. Takt time is calculated by dividing the daily total production time by daily customer demand.

**Figure 5.** *Value stream mapping icons.*


### **5. Sector specific applications of VSM**

For a better understanding of the subject, it will be useful to support the VSM method with examples. In line with this purpose, two examples, one of them from service sector and other from production sector are given.

#### **5.1 Service sector example**

The first example is from the service sector. The graduation, specifically the exmatriculation process of university students is selected. As aforementioned earlier in this chapter, the first stage of the VSM method is the identification of the product/service family. Here; the exmatriculation process of a university is determined as the product family. Then, the current situation of the flow in this process is observed and the current state map (CSM) is created (**Figure 6**). As seen in **Figure 6**, there are 12 steps in this process. The flow starts with "transcript control" step and ends with "completion of process". In this map, various wastes stand out. For instance, unnecessary motions (meeting with advisor step), defects (meeting with advisor step), over processing (paper-work and head of department steps), waiting (head of department and filling out the survey steps), and inventory between processes (between department secretary and filling out the survey steps). A future state map (FSM) is drawn in order to eliminate these wastes (**Figure 7**). The first suggestion is that, student information system should be used actively. Moreover, various lean methods are proposed to eliminate the wastes generated during the processes. These lean methods are 5S, Poka-Yoke, quality at the source, kaizen, balanced work flow,

**49**

**Figure 6.**

**Figure 7.**

*Current state map (service sector).*

(student) satisfaction is ensured.

*Future state map (service sector).*

**5.2 Production sector example**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

standardized work, SMED, inventory reduction and visual controls. If the CSM (**Figure 6**) and FSM (**Figure 7**) are compared simultaneously, it is possible to see the wastes and how to eliminate them. As a result, while continuous flow is achieved, the total time is reduced from 363.5 to 276.5 minutes. This indicates an improvement of 0.24% in the process. In addition, resources are used efficiently and customer

For the production sector application, a furniture factory is chosen. One of the sofa model (model A) produced in the furniture company is examined under VSM method (this example is derived from study of Dogan and Takcı [41]). Model A is now the product family of this example. As the second stage of VSM, the steps

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible DOI: http://dx.doi.org/10.5772/intechopen.83798*

#### **Figure 6.** *Current state map (service sector).*

*Lean Manufacturing and Six Sigma - Behind the Mask*

• *Lead time* (in days) is calculated by dividing the number of inventories

• *Cycle time* is expressed as the maximum time spent on a unit in each station. Cycle time is calculated with a simple formula: 1/output rate per hour in units.

For a better understanding of the subject, it will be useful to support the VSM method with examples. In line with this purpose, two examples, one of them from

The first example is from the service sector. The graduation, specifically the exmatriculation process of university students is selected. As aforementioned earlier in this chapter, the first stage of the VSM method is the identification of the product/service family. Here; the exmatriculation process of a university is determined as the product family. Then, the current situation of the flow in this process is observed and the current state map (CSM) is created (**Figure 6**). As seen in **Figure 6**, there are 12 steps in this process. The flow starts with "transcript control" step and ends with "completion of process". In this map, various wastes stand out. For instance, unnecessary motions (meeting with advisor step), defects (meeting with advisor step), over processing (paper-work and head of department steps), waiting (head of department and filling out the survey steps), and inventory between processes (between department secretary and filling out the survey steps). A future state map (FSM) is drawn in order to eliminate these wastes (**Figure 7**). The first suggestion is that, student information system should be used actively. Moreover, various lean methods are proposed to eliminate the wastes generated during the processes. These lean methods are 5S, Poka-Yoke, quality at the source, kaizen, balanced work flow,

between the processing steps into the daily demand.

service sector and other from production sector are given.

**5. Sector specific applications of VSM**

**5.1 Service sector example**

**Figure 5.**

*Value stream mapping icons.*

**48**

standardized work, SMED, inventory reduction and visual controls. If the CSM (**Figure 6**) and FSM (**Figure 7**) are compared simultaneously, it is possible to see the wastes and how to eliminate them. As a result, while continuous flow is achieved, the total time is reduced from 363.5 to 276.5 minutes. This indicates an improvement of 0.24% in the process. In addition, resources are used efficiently and customer (student) satisfaction is ensured.

### **5.2 Production sector example**

For the production sector application, a furniture factory is chosen. One of the sofa model (model A) produced in the furniture company is examined under VSM method (this example is derived from study of Dogan and Takcı [41]). Model A is now the product family of this example. As the second stage of VSM, the steps

#### *Lean Manufacturing and Six Sigma - Behind the Mask*

#### **Figure 8.** *Current state map (production sector).*

#### **Figure 9.** *Future state map (production sector).*

in the production phase of Model A are focused. The current state map (CSM) demonstrating this process is shown in **Figure 8**. There are eight production steps in CSM (**Figure 8**). Production flow starts with "crocking" and ends with "packaging". When the current state map is analyzed, it is seen that the total time is 1.49 days and the processing time is 594 seconds. By drawing the CSM, some problems have emerged in the production area. The main problems are as follows: intermediate inventories between the processes; unbalanced workload; time losses due to the inadequate supply of the material and time losses cause quality errors (average 9.62%); time losses due to layout problem, unnecessary transportation and deficiencies like material identification. Then, to eliminate the problems identified with the CSM, a future state map (FSM) is drawn (**Figure 9**). In the FSM, the Kanban system is established, the pull system is applied to prevent accumulated intermediate inventories between the processes and the material transfer is

**51**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

controlled by FIFO. In addition, Yamazumi is proposed for balancing the workload and minimizing the quality errors and establishment of the Kanban system makes it possible to prevent time losses in production due to the lack of timely supply of the materials. Finally, it may be preferable to use 5S and physical work redesign in order to prevent the time losses due to the layout problem and the deficiencies in the material identification. Analysis of the production process of model A by VSM method showed that continuous flow is achieved; a decrease of approximately 53% in the total time, a decrease of 30% in the processing time and a 36% improvement in the quality error rate. As in the example of the service sector, when the CSM (**Figure 8**) and FSM (**Figure 9**) for production process of model A are examined simultaneously, the wastes, errors, defects and at the same time, improvements in

Lean thinking is the general framework of the implementation of the lean philosophy in the production and service sectors [42]. As stated by Womack and Jones [8] *"lean thinking is lean because it provides a way to do more and more with less and less—less human effort, less equipment, less time, and less space—while coming closer and closer to providing customers with exactly what they want."* LT is an endless process and implementation of continuous improvement. For continuous improvement, researchers and professionals prefer various lean methods like VSM, 5S, SMED, balanced work flow, standardized work etc. The primary purpose of these methods

Value stream mapping is one of the most preferred methods in literature. This is the mapping of the whole process. Mapping the stages of a process, will assist to discover the opportunities for improvement and prevent the loss of time and money of stakeholders [43]. VSM applications, with the aim of eliminating waste are not restricted to a single business; it can also be applied to the supply chain by focusing on all the steps from the first supplier to the end customer. The essence of the matter is that, VSM can be effectively used in all processes if a product or service flow exists.

This chapter has focused on lean philosophy and lean methods, especially the VSM. The motive for the detailed examination of the VSM method is that VSM is the first step to overcome how the lean production will be applied. The reason why this method is first preferred is that the whole operation is seen as a holistic approach, and at the same time, it proposes a prescription to eliminate errors and/ or wastes. On the other hand, like many other methods, this method has also some limitations. Mapping complex systems with VSM can sometimes be difficult. At this point, large wastes or resources of wastes may be unnoticed. This can be a major problem in VSM, whose main goal is revealing and eliminating waste. Moreover, rather than using the VSM method alone, using with other lean methods will increase the reliability and efficiency of the results. To overcome these weaknesses, it is recommended to benefit from other methods together with the VSM method. For instance, theory of constraints, flowcharts, artificial intelligence and simulation

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

the processes can be clearly seen.

is to eliminate waste and ensure continuous flow.

are some of the methods that can be used with VSM.

**6. Discussion**

**7. Conclusion**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible DOI: http://dx.doi.org/10.5772/intechopen.83798*

controlled by FIFO. In addition, Yamazumi is proposed for balancing the workload and minimizing the quality errors and establishment of the Kanban system makes it possible to prevent time losses in production due to the lack of timely supply of the materials. Finally, it may be preferable to use 5S and physical work redesign in order to prevent the time losses due to the layout problem and the deficiencies in the material identification. Analysis of the production process of model A by VSM method showed that continuous flow is achieved; a decrease of approximately 53% in the total time, a decrease of 30% in the processing time and a 36% improvement in the quality error rate. As in the example of the service sector, when the CSM (**Figure 8**) and FSM (**Figure 9**) for production process of model A are examined simultaneously, the wastes, errors, defects and at the same time, improvements in the processes can be clearly seen.

### **6. Discussion**

*Lean Manufacturing and Six Sigma - Behind the Mask*

in the production phase of Model A are focused. The current state map (CSM) demonstrating this process is shown in **Figure 8**. There are eight production steps in CSM (**Figure 8**). Production flow starts with "crocking" and ends with "packaging". When the current state map is analyzed, it is seen that the total time is 1.49 days and the processing time is 594 seconds. By drawing the CSM, some problems have emerged in the production area. The main problems are as follows: intermediate inventories between the processes; unbalanced workload; time losses due to the inadequate supply of the material and time losses cause quality errors (average 9.62%); time losses due to layout problem, unnecessary transportation and deficiencies like material identification. Then, to eliminate the problems identified with the CSM, a future state map (FSM) is drawn (**Figure 9**). In the FSM, the Kanban system is established, the pull system is applied to prevent accumulated intermediate inventories between the processes and the material transfer is

**50**

**Figure 9.**

**Figure 8.**

*Current state map (production sector).*

*Future state map (production sector).*

Lean thinking is the general framework of the implementation of the lean philosophy in the production and service sectors [42]. As stated by Womack and Jones [8] *"lean thinking is lean because it provides a way to do more and more with less and less—less human effort, less equipment, less time, and less space—while coming closer and closer to providing customers with exactly what they want."* LT is an endless process and implementation of continuous improvement. For continuous improvement, researchers and professionals prefer various lean methods like VSM, 5S, SMED, balanced work flow, standardized work etc. The primary purpose of these methods is to eliminate waste and ensure continuous flow.

Value stream mapping is one of the most preferred methods in literature. This is the mapping of the whole process. Mapping the stages of a process, will assist to discover the opportunities for improvement and prevent the loss of time and money of stakeholders [43]. VSM applications, with the aim of eliminating waste are not restricted to a single business; it can also be applied to the supply chain by focusing on all the steps from the first supplier to the end customer. The essence of the matter is that, VSM can be effectively used in all processes if a product or service flow exists.

### **7. Conclusion**

This chapter has focused on lean philosophy and lean methods, especially the VSM. The motive for the detailed examination of the VSM method is that VSM is the first step to overcome how the lean production will be applied. The reason why this method is first preferred is that the whole operation is seen as a holistic approach, and at the same time, it proposes a prescription to eliminate errors and/ or wastes. On the other hand, like many other methods, this method has also some limitations. Mapping complex systems with VSM can sometimes be difficult. At this point, large wastes or resources of wastes may be unnoticed. This can be a major problem in VSM, whose main goal is revealing and eliminating waste. Moreover, rather than using the VSM method alone, using with other lean methods will increase the reliability and efficiency of the results. To overcome these weaknesses, it is recommended to benefit from other methods together with the VSM method. For instance, theory of constraints, flowcharts, artificial intelligence and simulation are some of the methods that can be used with VSM.

*Lean Manufacturing and Six Sigma - Behind the Mask*

## **Author details**

Nuri Ozgur Dogan and Burcu Simsek Yagli\* Department of Business Administration, Nevsehir Hacı Bektas Veli University, Nevsehir, Turkey

\*Address all correspondence to: burcusimsek@nevsehir.edu.tr

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**53**

*Value Stream Mapping: A Method That Makes the Waste in the Process Visible*

service industry: A review of the current knowledge. Production. 2015;**25**(3): 529-541. DOI: 10.1590/0103-6513.079012

[11] Cohen RI. Lean methodology in health care. Chest. 2018;**154**(6):1448-1454. DOI: 10.1016/j.chest.2018.06.005

Simulation-Based Lean Six-Sigma and Design for Six-Sigma. New Jersey: John Wiley & Sons; 2006. DOI:

[13] Melton T. The benefits of lean manufacturing: What lean thinking has to offer the process industries. Chemical Engineering Research and Design. 2005;**83**(6):662-673. DOI: 10.1205/

[14] Ingelsson P, Mårtensson A.

Measuring the importance and practices of Lean values. The TQM Journal. 2014;**26**(5):463-474. DOI: 10.1108/

[15] Ballard G, Kim YW, Jang JW, Liu M. Road Map for Lean Implementation at the Project Level. Austin: The Construction Industry Institute, The

[16] Liker JK. The 14 Principles of the Toyota Way: An Executive Summary of the Culture behind TPS. The Toyota

[17] Koskela L. Application of the New Production Philosophy to Construction. Vol. 72. Stanford: Stanford University;

[18] King PL, King JS. Value Stream Mapping for the Process Industries:

[10] Aziz RF, Hafez SM. Applying lean thinking in construction and performance improvement. Alexandria Engineering Journal. 2013;**52**(4):679-695.

DOI: 10.1016/j.aej.2013.04.008

[12] El-Haik B, Al-Aomar R.

10.1002/0470047720

cherd.04351

tqm-07-2012-0047

University of Texas: 2007

Way. Vol. 1; 2004. pp. 35-41

1992

*DOI: http://dx.doi.org/10.5772/intechopen.83798*

[1] Dhandapani V, Potter A, Naim M. Applying lean thinking: A case study of an Indian steel plant. International Journal of Logistics Research and Applications. 2004;**7**(3):239-250. DOI: 10.1080/13675560412331298491

[2] Radnor ZJ, Holweg M, Waring J. Lean in healthcare: The unfilled promise? Social Science & Medicine. 2012;**74**(3):364-371. DOI: 10.1016/j.

[3] Bhasin S, Burcher P. Lean viewed as a philosophy. Journal of Manufacturing Technology Management. 2006;**17**(1): 56-72. DOI: 10.1108/17410380610639506

[4] Al-Aomar R, Hussain M. An assessment of adopting lean

techniques in the construct of hotel supply chain. Tourism Management. 2018;**69**:553-565. DOI: 10.1016/j.

[5] Bonaccorsi A, Carmignani G, Zammori F.

Service value stream management (SVSM): Developing lean thinking in the service industry. Journal of Service Science and Management. 2011;**4**(04):428. DOI:

[6] Womack JP, Jones DT. Beyond Toyota: How to root out waste and pursue perfection. Harvard Business

[7] Vlachos I, Bogdanovic A. Lean thinking in the European hotel industry. Tourism Management. 2013;**36**:354-363. DOI: 10.1016/j.tourman.2012.10.007

[8] Womack JP, Jones DT. Lean thinking—Banish waste and create wealth in your corporation. The Journal of the Operational Research Society. 1997;**48**(11):1148-1148. DOI: 10.1057/

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### **References**

*Lean Manufacturing and Six Sigma - Behind the Mask*

**52**

**Author details**

Nevsehir, Turkey

provided the original work is properly cited.

Nuri Ozgur Dogan and Burcu Simsek Yagli\*

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Department of Business Administration, Nevsehir Hacı Bektas Veli University,

\*Address all correspondence to: burcusimsek@nevsehir.edu.tr

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[5] Bonaccorsi A, Carmignani G, Zammori F. Service value stream management (SVSM): Developing lean thinking in the service industry. Journal of Service Science and Management. 2011;**4**(04):428. DOI: 10.4236/jssm.2011.44048

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[39] Mazur LM, Chen SJG. Understanding and reducing the medication delivery waste via systems mapping and analysis. Health Care Management Science. 2008;**11**(1):55-65. DOI: 10.1007/s10729-007-9024-9

ASQ Quality Press; 2006

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*Lean Manufacturing and Six Sigma - Behind the Mask*

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**57**

**Chapter 5**

**Abstract**

**1. Introduction**

surreal, i.e., some introduced, unnatural shade.

of Dumps

*Andrey Alexandrovich Richter*

Some Aspects of Visual Detection

*The chapter describes some aspects of the method of visual detection of landfills from space images as one of the directions of remote monitoring of landfills.*

Waste location objects (unauthorized landfills, landfills, waste heaps, etc.) from the point of view of visual detection have deciphering characteristics, primarily shapes and textures that distinguish them from objects of the earth's surface of other types in space images. The technology of visual detection of landfills includes a number of issues, in particular: the definition, presentation, and analysis of deciphering features in visible images, algorithms and approaches for visual detection of landfills, deductive analysis as a way to get the maximum of productive information from the minimum "raw" only on the images themselves, research and mapping of landfills through interactive maps (Google, Yandex, etc.), and classification, texture, and structure of landfills and the environment from the point of view of visual detection from space images, etc. This chapter considers only some aspects.

**Keywords:** dump, landfill, littering, visual detection, visual interpretation, space monitoring, space image, logical analysis, deciphering signs, mapping

Littering "incarnates" in various forms—from chaotically debris scattered over some surface to the "civilized" garbage Everest towering above the cities. The beauty of nature is truly extraordinary and unique; it can be described by countless many paintings, unique, emphasizing more and more of its shades. With the development of scientific and technological progress, a new phenomenon appeared that has an anthropogenic character but adorns nature along with its natural "colors," such as birch groves, fresh lakes, flood meadows, etc. Dumps can be a truly fascinating, spectacular spectacle, and the landscapes painted from them can claim painting exhibitions in galleries as a whole art direction. However, when you see a large dump and a small grove in one projection, something inside suggests the unnaturalness and absurdity of such interaction of artistic images. Such landscapes are

An absurd combination takes place in many aspects of modern human existence, for example, in the human consciousness, where completely dissimilar, incompatible components accumulate. And with all this, the processes of this consciousness are continuously occurring, due to which the activity of the unpredictable kind is "released." The physicochemical processes in landfills are similar; in particular, the

### **Chapter 5**

## Some Aspects of Visual Detection of Dumps

*Andrey Alexandrovich Richter*

*The chapter describes some aspects of the method of visual detection of landfills from space images as one of the directions of remote monitoring of landfills.*

### **Abstract**

Waste location objects (unauthorized landfills, landfills, waste heaps, etc.) from the point of view of visual detection have deciphering characteristics, primarily shapes and textures that distinguish them from objects of the earth's surface of other types in space images. The technology of visual detection of landfills includes a number of issues, in particular: the definition, presentation, and analysis of deciphering features in visible images, algorithms and approaches for visual detection of landfills, deductive analysis as a way to get the maximum of productive information from the minimum "raw" only on the images themselves, research and mapping of landfills through interactive maps (Google, Yandex, etc.), and classification, texture, and structure of landfills and the environment from the point of view of visual detection from space images, etc. This chapter considers only some aspects.

**Keywords:** dump, landfill, littering, visual detection, visual interpretation, space monitoring, space image, logical analysis, deciphering signs, mapping

### **1. Introduction**

Littering "incarnates" in various forms—from chaotically debris scattered over some surface to the "civilized" garbage Everest towering above the cities. The beauty of nature is truly extraordinary and unique; it can be described by countless many paintings, unique, emphasizing more and more of its shades. With the development of scientific and technological progress, a new phenomenon appeared that has an anthropogenic character but adorns nature along with its natural "colors," such as birch groves, fresh lakes, flood meadows, etc. Dumps can be a truly fascinating, spectacular spectacle, and the landscapes painted from them can claim painting exhibitions in galleries as a whole art direction. However, when you see a large dump and a small grove in one projection, something inside suggests the unnaturalness and absurdity of such interaction of artistic images. Such landscapes are surreal, i.e., some introduced, unnatural shade.

An absurd combination takes place in many aspects of modern human existence, for example, in the human consciousness, where completely dissimilar, incompatible components accumulate. And with all this, the processes of this consciousness are continuously occurring, due to which the activity of the unpredictable kind is "released." The physicochemical processes in landfills are similar; in particular, the

composition of substances released from them in a liquid, solid, or gaseous state is just as unpredictable. This, i.e., a wide range of options for their "behavior," is dangerous, first of all.

Visual detection is one of the simplest and most widely available methods of monitoring, first of all, space monitoring. The essence of it is to study object on the image in an interactive mode, without developing and using special programs that automate this process. Images can be aerial photographs, space images, or fragments thereof; photographs of objects of study, taken with cameras; maps of objects on various maps, etc.

### **2. Dumps on high-resolution space images**

#### **2.1 Texture of dumps in images of high resolution**

*Dumps* (*waste location objects*, *WLO*) refer to the observed objects, and they can be detected by the methods of space monitoring. In addition, WLO is easily detected in visible images, because they stand out against the background of *ambient environment* (AE) and have a characteristic texture.

At the same time, the *texture* of dumps is variable and diverse; it depends, first of all, on (1) the time of year and the day (the angle of incidence of the sun's rays), (2) the size, (3) the class of WLO, (4) component composition, (5) location region, (6) screening of the WLO surface, and (7) spatial resolution, which in Google Earth is regulated by scaling.

From the point of view of visual detection, the texture is characterized by some verbal description. For example, a typical WLO and its texture are shown in **Figure 1**. A *typical* WLO texture can be specified as follows: a combination of random and close shades from white to dark gray, in some places—with a small admixture of red. The first group of shades (from white to dark gray) is the main one, the dominant one, the second (red)—non-main, secondary. When red is applied in some places, various impurities are formed on the basic shades, such as pink, reddish, lilac, etc.

#### **2.2 WLO and its structure in the Google Earth**

We will show the structure of WLO and its AE in the example of the Torbeevo landfill—**Figure 2**: WLO (1) and its AE (2), conditionally allocated as a rectangle. In the AE zone, there is a settlement of the same name—the Torbeevo village. Also the landfill is surrounded by the villages Rusavkino-Romanovo, Rusavkino-Popovschino, Polushkino, Novy Milet, and Michurinets and other settlements of Balashikha and Lyubertsy districts. Many of them, it turns out, are located in the sanitary zone of the landfill, which is a direct violation of the rules *for planning*,

**Figure 1.**

*Typical WLO (a) and typical waste texture (b) WLO in the vicinity of the Kuchino landfill in the Moscow region, July 5, 2010 (Google Earth).*

**59**

**Figure 3.**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

**Figure 2.**

*operation*, *and recultivation* (POR) of landfills [1]; by the rules the nearest apartment house to the landfill should be no less than 1 km from it. In fact, this is a minor violation compared to others, which are also observed by visual detection in the

*Isolation of WLO and its surroundings by the example of the Torbeevo landfill (Lyubertsy district, Google Earth).*

The surface of the Earth has changed technologically very strongly over the past few years (**Figure 3**). In particular, (1) the dump itself has grown several times; (2) where there were farms, now there is the economic zone of the landfill with all the consequences; (3) the production of soil for storing waste and expanding the landfill occurs in large areas; (4) the thin forest belt has been cut down and large areas of fertile land have been destroyed; (5) the seizure of new areas under construction and production of soil and there are other features of the changes. It should be noted that the area covered by vegetation (forest, shrubby, grassy) steadily decreases with time in principle, replacing anthropogenic objects. So, the areas of forest plantations are insignificant in comparison with the areas of forest harvesting. A stable decrease in the area of vegetation coverage is also seen in the

The composition of the AE of the WLO Torbeevo landfill includes (see **Figure 2**) a high incidence of human settlements, a "dirty" storage area (I), a polluted river Chernaya (II), shaky roads (III), the remains of the former livestock farm—stable (IV), fading agricultural fields (V), and other objects of natural and anthropogenic origins. It is noteworthy that many objects of the same class are attached to the environment of various landfills, such as cemeteries (AE of the landfills Kuchino, Dolgoprudny, etc.)

In general, AE can be represented by objects of numerous classes: (1) *natural objects*—water (rivers, reservoirs), forest (forest massifs, plantings), grassy (meadows, glades), and other zones; (2) *anthropogenic objects*—settlements (villages, settlements), *industrial* (factories, plants), *agricultural* (animal farms, agricultural fields), service areas (filling stations, parking lots), *transport* (roads, railways), and other zones.

*Changes in the vicinity of the Torbeevo landfill: (a) June 2003 and (b) April 2014 (Google Earth).*

and agricultural areas (AE of the landfills Lisya Gora, Torbeevo, etc.).

Google Earth program (this will be discussed later) [2–4].

vicinity of the WLO (not shown in the figures).

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

*Lean Manufacturing and Six Sigma - Behind the Mask*

**2. Dumps on high-resolution space images**

**2.1 Texture of dumps in images of high resolution**

*ent environment* (AE) and have a characteristic texture.

**2.2 WLO and its structure in the Google Earth**

dangerous, first of all.

regulated by scaling.

composition of substances released from them in a liquid, solid, or gaseous state is just as unpredictable. This, i.e., a wide range of options for their "behavior," is

Visual detection is one of the simplest and most widely available methods of monitoring, first of all, space monitoring. The essence of it is to study object on the image in an interactive mode, without developing and using special programs that automate this process. Images can be aerial photographs, space images, or fragments thereof; photographs of objects of study, taken with cameras; maps of objects on various maps, etc.

*Dumps* (*waste location objects*, *WLO*) refer to the observed objects, and they can be detected by the methods of space monitoring. In addition, WLO is easily detected in visible images, because they stand out against the background of *ambi-*

At the same time, the *texture* of dumps is variable and diverse; it depends, first of all, on (1) the time of year and the day (the angle of incidence of the sun's rays), (2) the size, (3) the class of WLO, (4) component composition, (5) location region, (6) screening of the WLO surface, and (7) spatial resolution, which in Google Earth is

From the point of view of visual detection, the texture is characterized by some verbal description. For example, a typical WLO and its texture are shown in **Figure 1**. A *typical* WLO texture can be specified as follows: a combination of random and close shades from white to dark gray, in some places—with a small admixture of red. The first group of shades (from white to dark gray) is the main one, the dominant one, the second (red)—non-main, secondary. When red is applied in some places, various

We will show the structure of WLO and its AE in the example of the Torbeevo landfill—**Figure 2**: WLO (1) and its AE (2), conditionally allocated as a rectangle. In the AE zone, there is a settlement of the same name—the Torbeevo village. Also the landfill is surrounded by the villages Rusavkino-Romanovo, Rusavkino-Popovschino, Polushkino, Novy Milet, and Michurinets and other settlements of Balashikha and Lyubertsy districts. Many of them, it turns out, are located in the sanitary zone of the landfill, which is a direct violation of the rules *for planning*,

*Typical WLO (a) and typical waste texture (b) WLO in the vicinity of the Kuchino landfill in the Moscow* 

impurities are formed on the basic shades, such as pink, reddish, lilac, etc.

**58**

**Figure 1.**

*region, July 5, 2010 (Google Earth).*

**Figure 2.** *Isolation of WLO and its surroundings by the example of the Torbeevo landfill (Lyubertsy district, Google Earth).*

*operation*, *and recultivation* (POR) of landfills [1]; by the rules the nearest apartment house to the landfill should be no less than 1 km from it. In fact, this is a minor violation compared to others, which are also observed by visual detection in the Google Earth program (this will be discussed later) [2–4].

The surface of the Earth has changed technologically very strongly over the past few years (**Figure 3**). In particular, (1) the dump itself has grown several times; (2) where there were farms, now there is the economic zone of the landfill with all the consequences; (3) the production of soil for storing waste and expanding the landfill occurs in large areas; (4) the thin forest belt has been cut down and large areas of fertile land have been destroyed; (5) the seizure of new areas under construction and production of soil and there are other features of the changes. It should be noted that the area covered by vegetation (forest, shrubby, grassy) steadily decreases with time in principle, replacing anthropogenic objects. So, the areas of forest plantations are insignificant in comparison with the areas of forest harvesting. A stable decrease in the area of vegetation coverage is also seen in the vicinity of the WLO (not shown in the figures).

The composition of the AE of the WLO Torbeevo landfill includes (see **Figure 2**) a high incidence of human settlements, a "dirty" storage area (I), a polluted river Chernaya (II), shaky roads (III), the remains of the former livestock farm—stable (IV), fading agricultural fields (V), and other objects of natural and anthropogenic origins.

It is noteworthy that many objects of the same class are attached to the environment of various landfills, such as cemeteries (AE of the landfills Kuchino, Dolgoprudny, etc.) and agricultural areas (AE of the landfills Lisya Gora, Torbeevo, etc.).

In general, AE can be represented by objects of numerous classes: (1) *natural objects*—water (rivers, reservoirs), forest (forest massifs, plantings), grassy (meadows, glades), and other zones; (2) *anthropogenic objects*—settlements (villages, settlements), *industrial* (factories, plants), *agricultural* (animal farms, agricultural fields), service areas (filling stations, parking lots), *transport* (roads, railways), and other zones.

**Figure 3.** *Changes in the vicinity of the Torbeevo landfill: (a) June 2003 and (b) April 2014 (Google Earth).*

In this case, you can select objects of different levels—objects of a lower level enter objects of a higher level. So, trees are objects of the lower level; a forestry array made up of trees is an object of a higher one; house is the object of the lower level, the village—the upper one.

Similarly, WLO are structurally complex objects (top-level objects) made up of "cubes" of simpler objects (lower-level objects). Let us consider in more detail the structure of a WLO in the example of the Torbeevo landfill (**Figure 4a**).

The *structural object* can be cut in the first approximation, as shown in **Figure 4a**. The structure can be represented by polygonal areas and/or corresponding labels (1–4). We have four zones (sections): (1) storage area, (2) landfill area for storage of waste, (3) economic zone, and (4) zone for expanding the boundaries of the landfill for storage of waste (presumably).

In turn, each zone is divided and/or contains more private objects. For example, the economic zone is represented by numerous *technoobjects* (office, industrial buildings, warehouses, residential objects—"trailers," parking lots, etc.) and other territories (in particular, for the disposal of specialized waste).

Thus the territory of the WLO and its AE can be represented in the form of a map consisting of many layers. For the WLO map, the Torbeevo landfill is one of the layers—dividing it into the main zones. You can create other layers, for example, "cluttering the vicinity of the WLO" (**Figure 4b**), "transport system" (**Figure 4c**), "anomalous zones," "territories with a homogeneous texture," etc.

In **Figure 4c**: (1) access roads to the landfill (outer part of the transport system), (2) main road, (3) serpentine, (4) secondary roads, (5) road junctions of the economic zone, (6) roads on the surface of the landfill, (7) transportation nodes. The transport system establishes routes, first of all, for garbage trucks, bunker trucks, scrapers, and other garbage equipment. Each road leads in different ways, one of which is optimal in length (see the theory of dynamic programming and other applications of the theory of optimization), from the external environment to this or that object, be it building, cluttering, sand mounds, etc.

The *WLO card* of a *private area* is a map of the land surface on which an WLO array is located within the territory of the possession of individuals or legal entities (enterprises, organizations, cooperatives, etc.) and relationships with infrastructure objects (roads, fences, buildings, structures, etc.). **Figure 5** shows examples of WLO maps showing the WLOs within the general and internal boundaries of a private area. The locations of the landfills in the observation area are marked in red tags: the territory of the business park to the west of vil. Motyakovo, northern (a) and southern (b) parts.

#### **2.3 The dynamics of WLO and the environment of the WLO**

The state of the NSO from the point of view of visual detection can be estimated in various ways, for example: (1) areas occupied by vegetation and their variation over time; (2) soil degradation—bogging, salinization, etc.; (3) changes in the object

**Figure 4.**

*Structure of the Torbeevo landfill: (a) the division of the territory in the first approximation, (b) the main dumps in the vicinity, and (c) transport system (Google Earth).*

**61**

**Figure 6.**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

visual detection, etc., are used.

**Figure 5.**

composition of the territory; (4) anomalous zones in the vicinity of the WLO; (5) compliance with the rules of the POR of the WLO; and (6) quality of vegetation. To study the state of territories, not necessarily WLO, in addition to the "visual" method, methods of *inductive* and *deductive analysis*, combining space and field

*Maps of the WLO of private territories on the example of industrial zones near the Motyakovo village,* 

We will analyze the state of AE on the example of a WLO Kuchino landfill, Moscow region, the Balashikha district, in the common people—the Fenino dump

**Figure 6** shows the areas of general changes in the vicinity of the landfill: (1–4) vegetation reduction, (5–8) vegetation increase, (9–13) landfill expansion (breadth and height), and (14, 15) expansion of the Fenino cemetery. Every change has its own cause. For example, changes 3 have anthropogenic reasons: the need for deforestation to prepare additional areas for the development of soil for backfilling. Then the working zone can be conditionally divided into the current (4) and reserve (technologically still unchanged natural areas in the vicinity of the landfill). Changes (5–8) have a natural (natural) cause: overgrowing of the slopes of the landfill by vegetation. In general, *overgrowing* is one of the protective functions of

The warehousing section itself has a lot of structural elements, the so-called storage cards (see **Figure 7**). Waste is filled in by cards "line by line," i.e., successively first in width, and then filled to the next level of height. The structure of cards of one level differs from the structure of the maps of the other—like brickwork, where the bricks of the lower level are lapped by bricks of the uppermost for greater stability of the structure. Due to the duration of the filling of certain cards, other cards (already filled) begin to overgrow with vegetation (see **Figure 6b**)

*Changes in the vicinity of the Kuchino landfill site from June 11, 2003 (a) to July 13, 2014 (b) (Google Earth).*

in honor of the adjoining inhabited locality of the Fenino village.

*Lyubertsy district of the Moscow region (red tags) [Google Earth].*

the environment from various negative impacts on it, such as WLO.

**Figure 5.**

*Lean Manufacturing and Six Sigma - Behind the Mask*

the village—the upper one.

for storage of waste (presumably).

In this case, you can select objects of different levels—objects of a lower level enter objects of a higher level. So, trees are objects of the lower level; a forestry array made up of trees is an object of a higher one; house is the object of the lower level,

Similarly, WLO are structurally complex objects (top-level objects) made up of "cubes" of simpler objects (lower-level objects). Let us consider in more detail the

The *structural object* can be cut in the first approximation, as shown in **Figure 4a**. The structure can be represented by polygonal areas and/or corresponding labels (1–4). We have four zones (sections): (1) storage area, (2) landfill area for storage of waste, (3) economic zone, and (4) zone for expanding the boundaries of the landfill

In turn, each zone is divided and/or contains more private objects. For example,

Thus the territory of the WLO and its AE can be represented in the form of a map consisting of many layers. For the WLO map, the Torbeevo landfill is one of the layers—dividing it into the main zones. You can create other layers, for example, "cluttering the vicinity of the WLO" (**Figure 4b**), "transport system" (**Figure 4c**),

In **Figure 4c**: (1) access roads to the landfill (outer part of the transport system), (2) main road, (3) serpentine, (4) secondary roads, (5) road junctions of the economic zone, (6) roads on the surface of the landfill, (7) transportation nodes. The transport system establishes routes, first of all, for garbage trucks, bunker trucks, scrapers, and other garbage equipment. Each road leads in different ways, one of which is optimal in length (see the theory of dynamic programming and other applications of the theory of optimization), from the external environment

The *WLO card* of a *private area* is a map of the land surface on which an WLO array is located within the territory of the possession of individuals or legal entities (enterprises, organizations, cooperatives, etc.) and relationships with infrastructure objects (roads, fences, buildings, structures, etc.). **Figure 5** shows examples of WLO maps showing the WLOs within the general and internal boundaries of a private area. The locations of the landfills in the observation area are marked in red tags: the territory of the business park to the west of vil. Motyakovo, northern (a) and southern (b) parts.

The state of the NSO from the point of view of visual detection can be estimated in various ways, for example: (1) areas occupied by vegetation and their variation over time; (2) soil degradation—bogging, salinization, etc.; (3) changes in the object

*Structure of the Torbeevo landfill: (a) the division of the territory in the first approximation, (b) the main* 

the economic zone is represented by numerous *technoobjects* (office, industrial buildings, warehouses, residential objects—"trailers," parking lots, etc.) and other

territories (in particular, for the disposal of specialized waste).

"anomalous zones," "territories with a homogeneous texture," etc.

to this or that object, be it building, cluttering, sand mounds, etc.

**2.3 The dynamics of WLO and the environment of the WLO**

*dumps in the vicinity, and (c) transport system (Google Earth).*

structure of a WLO in the example of the Torbeevo landfill (**Figure 4a**).

**60**

**Figure 4.**

*Maps of the WLO of private territories on the example of industrial zones near the Motyakovo village, Lyubertsy district of the Moscow region (red tags) [Google Earth].*

composition of the territory; (4) anomalous zones in the vicinity of the WLO; (5) compliance with the rules of the POR of the WLO; and (6) quality of vegetation.

To study the state of territories, not necessarily WLO, in addition to the "visual" method, methods of *inductive* and *deductive analysis*, combining space and field visual detection, etc., are used.

We will analyze the state of AE on the example of a WLO Kuchino landfill, Moscow region, the Balashikha district, in the common people—the Fenino dump in honor of the adjoining inhabited locality of the Fenino village.

**Figure 6** shows the areas of general changes in the vicinity of the landfill: (1–4) vegetation reduction, (5–8) vegetation increase, (9–13) landfill expansion (breadth and height), and (14, 15) expansion of the Fenino cemetery. Every change has its own cause. For example, changes 3 have anthropogenic reasons: the need for deforestation to prepare additional areas for the development of soil for backfilling. Then the working zone can be conditionally divided into the current (4) and reserve (technologically still unchanged natural areas in the vicinity of the landfill). Changes (5–8) have a natural (natural) cause: overgrowing of the slopes of the landfill by vegetation. In general, *overgrowing* is one of the protective functions of the environment from various negative impacts on it, such as WLO.

The warehousing section itself has a lot of structural elements, the so-called storage cards (see **Figure 7**). Waste is filled in by cards "line by line," i.e., successively first in width, and then filled to the next level of height. The structure of cards of one level differs from the structure of the maps of the other—like brickwork, where the bricks of the lower level are lapped by bricks of the uppermost for greater stability of the structure. Due to the duration of the filling of certain cards, other cards (already filled) begin to overgrow with vegetation (see **Figure 6b**)

**Figure 6.** *Changes in the vicinity of the Kuchino landfill site from June 11, 2003 (a) to July 13, 2014 (b) (Google Earth).*

**Figure 7.**

*Structure of the landfill site for the Kuchino landfill, August 16, 2011: (a) on the map (Google Earth) and (b) schematically.*

and change their texture. But—for a while, because subsequently, the overgrown map will be covered by a new storage map. So at different periods of the life of the landfill, it consists of the current storage zone and the overgrowing zone where storage does not occur.

Parallel to this, the filling of the landfill takes place in the queues of storage. This explains the unevenness of the polygon contour, more precisely, the fragments of the storage site carried out in different directions (see 9 and 10 for **Figure 6b**). These fragments, mainly, are caused by the queues of storage—new territories adjacent to the landfill, planned and prepared for a new "portion" of waste disposal. Knowing these "bulges," we can assume a story, i.e., the order of waste storage in retrospect. In **Figure 6a**, the storage in site 9 is at the initial stage—this state of the site can be called an extension of the landfill boundaries.

By the principle of storage queues, not only NEOs are expanding but almost all anthropogenic objects, such as populated areas, cemeteries, agricultural and park areas, etc. In particular, the Fenino cemetery for 11 years has expanded in two directions: to the northwest and southeast—see plots 14 and 15 in **Figure 6b**.

Many anthropogenic objects are close to each other and in structure (**Figure 8**). In particular, the structure of the cemetery (a) is similar to the structure of the settlement (b).

In the figure, for example, three classes of objects are distinguished: (1) ownership areas, (2) plantations, and (3) access roads. The difference is only in the sizes of structural cells—for cemeteries these areas are smaller than for settlements.

**63**

**Figure 9.**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

sign of a negative impact on the soil.

visible). It was an ecologically clean and favorable area.

landfill in place of an already existing village.

areas and landfills), new roads, etc.

within the limits of its garden plot).

From the point of view of visual detection, the state of the soil is characterized by (1) technological changes in the territory (changes in infrastructure); (2) the state of vegetation as a sign of the state of the soil; (3) change in the state of the soil, improvement (enrichment) or deterioration (degradation); (4) the surface state as a sign of internal processes in the soil; and (5) abnormal zones on the surface as a sure

The landfill arose in the 1960s, but satellite imagery of high resolution arose only

in the 1980's. And it is not possible to investigate the landfill from space at birth from the very beginning. Therefore, historical references and opinions of history eyewitnesses (in particular, the residents of Fenino) are resorted to. According to their opinions, the dump is formed on the site of the former clay quarries. And the quarry was deep water and represented a resort zone, popular among the inhabitants of the Moscow region (in **Figure 6a**, the rest of the former water quarry is

The Fenino village is an ancient landfill, at least because the formation of a village on the site of an already existing landfill is less likely than the formation of a

If we confine ourselves to a narrow interval of time (from 2003 to 2014), then **Figure 6** shows that a number of technological changes occurred. And most intensively technologically the neighborhoods of the landfill have changed and not the remote neighborhoods. This range includes the expansion of the village and the landfill, the emergence of new buildings (in the expansion zones and former village

*Technological degradation*, we believe, occurs where the natural root system of the soil is disturbed (see Sections 2 and 4 in **Figure 6**). In general, the forms of degradation associated with the WLO include (1) technological (including deforestation), (2) bogging, (3) salinity, (4) desertification, and (5) littering. But unlike other forms, technological degradation arises abruptly. The source of technological degradation may be utilities or the private sector. In the first case, technological degradation occurs on a large territory and in the second—on an insignificant (e.g.,

Different forms of soil degradation are shown on the fragment of the AE landfill—**Figure 9**: (1) *water logging*, (2 and 3) unknown forms of degradation

*Forms of soil degradation in the vicinity of the Kuchino landfill, July 5, 2010 (Google Earth).*

**Figure 8.** *Structural objects: (a) Fenino cemetery and (b) the Fenino village (fragment) [Google Earth].*

#### *Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

*Lean Manufacturing and Six Sigma - Behind the Mask*

storage does not occur.

**Figure 7.**

*schematically.*

settlement (b).

**62**

**Figure 8.**

*Structural objects: (a) Fenino cemetery and (b) the Fenino village (fragment) [Google Earth].*

and change their texture. But—for a while, because subsequently, the overgrown map will be covered by a new storage map. So at different periods of the life of the landfill, it consists of the current storage zone and the overgrowing zone where

*Structure of the landfill site for the Kuchino landfill, August 16, 2011: (a) on the map (Google Earth) and (b)* 

Parallel to this, the filling of the landfill takes place in the queues of storage. This explains the unevenness of the polygon contour, more precisely, the fragments of the storage site carried out in different directions (see 9 and 10 for **Figure 6b**). These fragments, mainly, are caused by the queues of storage—new territories adjacent to the landfill, planned and prepared for a new "portion" of waste disposal. Knowing these "bulges," we can assume a story, i.e., the order of waste storage in retrospect. In **Figure 6a**, the storage in site 9 is at the initial stage—this state of the

By the principle of storage queues, not only NEOs are expanding but almost all anthropogenic objects, such as populated areas, cemeteries, agricultural and park areas, etc. In particular, the Fenino cemetery for 11 years has expanded in two direc-

Many anthropogenic objects are close to each other and in structure (**Figure 8**).

In the figure, for example, three classes of objects are distinguished: (1) ownership areas, (2) plantations, and (3) access roads. The difference is only in the sizes of structural cells—for cemeteries these areas are smaller than for settlements.

In particular, the structure of the cemetery (a) is similar to the structure of the

tions: to the northwest and southeast—see plots 14 and 15 in **Figure 6b**.

site can be called an extension of the landfill boundaries.

From the point of view of visual detection, the state of the soil is characterized by (1) technological changes in the territory (changes in infrastructure); (2) the state of vegetation as a sign of the state of the soil; (3) change in the state of the soil, improvement (enrichment) or deterioration (degradation); (4) the surface state as a sign of internal processes in the soil; and (5) abnormal zones on the surface as a sure sign of a negative impact on the soil.

The landfill arose in the 1960s, but satellite imagery of high resolution arose only in the 1980's. And it is not possible to investigate the landfill from space at birth from the very beginning. Therefore, historical references and opinions of history eyewitnesses (in particular, the residents of Fenino) are resorted to. According to their opinions, the dump is formed on the site of the former clay quarries. And the quarry was deep water and represented a resort zone, popular among the inhabitants of the Moscow region (in **Figure 6a**, the rest of the former water quarry is visible). It was an ecologically clean and favorable area.

The Fenino village is an ancient landfill, at least because the formation of a village on the site of an already existing landfill is less likely than the formation of a landfill in place of an already existing village.

If we confine ourselves to a narrow interval of time (from 2003 to 2014), then **Figure 6** shows that a number of technological changes occurred. And most intensively technologically the neighborhoods of the landfill have changed and not the remote neighborhoods. This range includes the expansion of the village and the landfill, the emergence of new buildings (in the expansion zones and former village areas and landfills), new roads, etc.

*Technological degradation*, we believe, occurs where the natural root system of the soil is disturbed (see Sections 2 and 4 in **Figure 6**). In general, the forms of degradation associated with the WLO include (1) technological (including deforestation), (2) bogging, (3) salinity, (4) desertification, and (5) littering. But unlike other forms, technological degradation arises abruptly. The source of technological degradation may be utilities or the private sector. In the first case, technological degradation occurs on a large territory and in the second—on an insignificant (e.g., within the limits of its garden plot).

Different forms of soil degradation are shown on the fragment of the AE landfill—**Figure 9**: (1) *water logging*, (2 and 3) unknown forms of degradation

**Figure 9.** *Forms of soil degradation in the vicinity of the Kuchino landfill, July 5, 2010 (Google Earth).*

(presumably *desertification* and *salinization* of the soil), (4) *littering*, and (5) *technological* degradation. For the degradation of the soil is characterized by an unnatural color of the earth's surface, violet (1), white (4), or brown (2, 3, 5). The presence of brown shades, especially in the summer season, against the background of green, means a reduced density of vegetation, i.e., inability of its full reproduction by soil.

Dilution of the vicinity of the WLO is caused, first of all, by the release of the filtrate to the surface of the earth, due to the excess of moisture in the soil and low reproduction of vegetation by soil. As can be seen from **Figure 10**, the filtration water flows from the base of the landfill and spreads in certain directions in the environment. In addition to the filtration reservoirs (1) and streams (2), they form traces of their current (3), and on the shores (4) of these reservoirs, virtually no vegetation grows (see also photo 2 in **Figure 11**). To reduce waterlogging, the soil is loaded with an additional layer of soil (5), which gives a temporary effect, due to the continuous accumulation of filtration in the soil (6). The filtration liquid can also take the form of channels (7), along the bottom of the storage site. Even in winter, numerous traces (8) of filtration processes remain on the surface of the earth (see **Figure 10**).

**Figure 10.**

*Components of filtration processes in the vicinity of the Kuchino landfill (Google Earth).*

**65**

the image.

processing algorithms.

**3.2 Image information**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

unknown graves with number plates (16 and 17).

given field of observation does not take place.

**3. The method of deductive analysis of space images**

**3.1 Features of the method of deductive analysis of images**

Visual observations on images can be verified by conducting verification, i.e., comparison of space and field (terrestrial) visualization data. For example, you can take a picture of the neighborhood of the landfill at its various points and compare the information obtained with the visual detection data in the Google Earth (**Figure 11**). **Figure 11** shows photographs of two anomalous areas: surface filtrate (2) and

Most, if not all, image processing methods and algorithms solve a very limited range of space monitoring tasks. In particular, in problems of region detection, some developed algorithm selects objects of a given type located in a certain territory at a certain point in time from the source image. In addition, automated and automatic algorithms are associated, mainly, with the detection, allocation, marking, and mapping of land surface areas and are not associated with the analysis of information on these images. Because types of natural and anthropogenic objects are huge, for each of them, algorithms are developed that are loaded onto cosmic images or their series, and a full and complete analysis of the space image and the

The advantage of classical algorithms of space monitoring is the automation of image processing, i.e., a large-scale survey of the area of observation using space images. But the reverse side of this "coin" is their main disadvantage—the limited possibilities for examining the area. Most of the information is not extracted from

To solve this problem, we propose a technique of *logical* (*deductive*) *analysis* of cosmic images, using the principles of logical reasoning on images and normalization of the results obtained. The proposed technique for the study of space images is based on visual observation of the image (using your own vision and reasoning for its interpretation). Logical analysis is obtaining the maximum amount of information from the minimum of initial data on a space image without the use of image

The merits of the method of deductive (*logical*) analysis of space images include the following: (1) the implementation of the methodology which does not require knowledge of programming, theory, and practice of image processing; (2) extraction of information that cannot be obtained by modern methods of image processing; and (3) no binding to

The disadvantages of the technique are (1) individual work with each image and the impossibility of partial or complete automation to date, (2) the need for manual and detailed image viewing, and (3) the inability to obtain the distribution of

The purpose of deductive analysis is as follows: (1) restoration of the history of the image; (2) restoration of information about the current picture; (3) predicting future processes on the surface of the earth, based on the given image; and (4) restoration of intermediate information (between neighboring shooting dates). Otherwise, the goal is some expansion of the space-time boundaries of the image.

Each image has several *types of information* (see **Figure 12**): (1) visible information, (2) invisible information, (3) information obtained by image processing, (4)

the type of images; deduction methods are the same for images of any kind.

surface state parameters, which is achieved by image processing.

**Figure 11.** *Photographs taken around the vicinity of the Kuchino landfill.*

#### *Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

*Lean Manufacturing and Six Sigma - Behind the Mask*

(presumably *desertification* and *salinization* of the soil), (4) *littering*, and (5) *technological* degradation. For the degradation of the soil is characterized by an unnatural color of the earth's surface, violet (1), white (4), or brown (2, 3, 5). The presence of brown shades, especially in the summer season, against the background of green, means a reduced density of vegetation, i.e., inability of its full reproduction by soil. Dilution of the vicinity of the WLO is caused, first of all, by the release of the filtrate to the surface of the earth, due to the excess of moisture in the soil and low reproduction of vegetation by soil. As can be seen from **Figure 10**, the filtration water flows from the base of the landfill and spreads in certain directions in the environment. In addition to the filtration reservoirs (1) and streams (2), they form traces of their current (3), and on the shores (4) of these reservoirs, virtually no vegetation grows (see also photo 2 in **Figure 11**). To reduce waterlogging, the soil is loaded with an additional layer of soil (5), which gives a temporary effect, due to the continuous accumulation of filtration in the soil (6). The filtration liquid can also take the form of channels (7), along the bottom of the storage site. Even in winter, numerous traces

(8) of filtration processes remain on the surface of the earth (see **Figure 10**).

*Components of filtration processes in the vicinity of the Kuchino landfill (Google Earth).*

**64**

**Figure 11.**

**Figure 10.**

*Photographs taken around the vicinity of the Kuchino landfill.*

Visual observations on images can be verified by conducting verification, i.e., comparison of space and field (terrestrial) visualization data. For example, you can take a picture of the neighborhood of the landfill at its various points and compare the information obtained with the visual detection data in the Google Earth (**Figure 11**).

**Figure 11** shows photographs of two anomalous areas: surface filtrate (2) and unknown graves with number plates (16 and 17).

### **3. The method of deductive analysis of space images**

#### **3.1 Features of the method of deductive analysis of images**

Most, if not all, image processing methods and algorithms solve a very limited range of space monitoring tasks. In particular, in problems of region detection, some developed algorithm selects objects of a given type located in a certain territory at a certain point in time from the source image. In addition, automated and automatic algorithms are associated, mainly, with the detection, allocation, marking, and mapping of land surface areas and are not associated with the analysis of information on these images. Because types of natural and anthropogenic objects are huge, for each of them, algorithms are developed that are loaded onto cosmic images or their series, and a full and complete analysis of the space image and the given field of observation does not take place.

The advantage of classical algorithms of space monitoring is the automation of image processing, i.e., a large-scale survey of the area of observation using space images. But the reverse side of this "coin" is their main disadvantage—the limited possibilities for examining the area. Most of the information is not extracted from the image.

To solve this problem, we propose a technique of *logical* (*deductive*) *analysis* of cosmic images, using the principles of logical reasoning on images and normalization of the results obtained. The proposed technique for the study of space images is based on visual observation of the image (using your own vision and reasoning for its interpretation). Logical analysis is obtaining the maximum amount of information from the minimum of initial data on a space image without the use of image processing algorithms.

The merits of the method of deductive (*logical*) analysis of space images include the following: (1) the implementation of the methodology which does not require knowledge of programming, theory, and practice of image processing; (2) extraction of information that cannot be obtained by modern methods of image processing; and (3) no binding to the type of images; deduction methods are the same for images of any kind.

The disadvantages of the technique are (1) individual work with each image and the impossibility of partial or complete automation to date, (2) the need for manual and detailed image viewing, and (3) the inability to obtain the distribution of surface state parameters, which is achieved by image processing.

The purpose of deductive analysis is as follows: (1) restoration of the history of the image; (2) restoration of information about the current picture; (3) predicting future processes on the surface of the earth, based on the given image; and (4) restoration of intermediate information (between neighboring shooting dates). Otherwise, the goal is some expansion of the space-time boundaries of the image.

#### **3.2 Image information**

Each image has several *types of information* (see **Figure 12**): (1) visible information, (2) invisible information, (3) information obtained by image processing, (4)

**Figure 12.**

*Image information: (a) information field (economic zone of the Timoshovo landfill, Noginsk district, Moscow region, Google Earth) and (b) types of information in the image.*

information obtained by deductive analysis, (5) general information obtained by image processing and deductive analysis, (6) recoverable information, (7) nonrecoverable information, and (8) all image information.

Deductive analysis is obtaining the maximum amount of information on a space image without the use of automated and automatic image processing algorithms.

To obtain visible information, *reasoning* is not required, but *logical thinking* itself takes place in any case. For example, in order to *see* a house in the image, it is necessary to have different images of houses in the mind, in the limit—a full *spectrum of types* of houses ("manual" method of managed classification). We assume that information 3 and 4 do not include information 1: that something can be simply seen; it is not necessary to resort to additional costs. However, to see something on a large number of images is less advisable than automating the process.

The reasoning behind deductive analysis has the following characteristics: (1) *Variability*—offers options for explaining a particular fact (details on the image). (2) *Distribution*—reasoning has a probabilistic and statistical character. (3) *Chain character*—one detail and one reasoning lead to another detail and another reasoning, etc. (4) *Detailing*—when interpreting one area of reasoning, they pass into its internal subdomain or conjugate domain. (5) *Algorithmization*—reasoning can be carried out on certain algorithms that allow to restore information. (6) *Schematization*—the system of reasoning is filled into some "vessel," i.e., takes the form of some model.

Deductive analysis (recovery of the maximum amount of hidden information from the image through its detailed observation) is the development of conventional image surveillance.

Deductive analysis is variable—options are offered for explaining a particular fact (details on the image). Those reasoning have a probabilistic-statistical and a chain character, because one detail and one reasoning lead to another detail and another reasoning and so on.

Processing of space images allows you to extract information hidden from the eyes. Human eyes are seen mainly in the visible spectrum, and information in the invisible spectrum is mostly hidden from the eyes. If a person had also seen in an invisible spectrum, he probably could have uncovered all the same information as when processing images but using only logical thinking (vision) and deductive analysis. But the processing would be required to speed up the extraction of information from the images by means of automation.

Deductive analysis, for the most part, allows you to obtain information that cannot be obtained by modern image processing methods. We believe that this "extension" can be used to interpret visible images or images on which most of the objects can be distinguished. However, there is some general information obtained by both methods. The boundaries of deductive analysis end where the boundaries of image processing begin and vice versa.

**67**

**Figure 13.**

*Events and states on the time axis.*

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

explaining any details on the image in space and time.

the presence of the information signal uij.

O for which there are no pictures, somehow identifying him.

**3.3 Objects and events**

*Information* can be visible or invisible and recoverable or non-recoverable. In the process of combining all the modern methods of image processing and *deduction* methods (and *induction*), some of the information on the image remains, in which it is impossible to extract for today—it is non-recoverable information. The limit of deductive analysis is the complete interpretation of the image, the possibility of

Information field of the image is introduced: information sources (Si), information objects (O), informational AE of source (IAE), boundary of AE (C) of some radius (r), information signals from the sources to the objects (u), and internal (I) and external (II) objects of a source. The *source of information* is some object in the image, which is known for the most information; it can be seen and recognized. These objects are highlighted in the first step of the analysis. A lot of information sources form an information basis of the image—these are the reference objects of the image, to which all information is bound to the information field. The information is identified in the vicinity of the region S1S2…Sn, where n is the number of sources. Each source has a certain *neighborhood* (IAE). Internal objects relative to the source belong to its AE and have a *connection* with it; external objects are on the contrary. The boundary separates the internal objects from the external ones. The connection of the source Si to the object Oij is expressed in

In the language of *object-oriented programming* (OOP), the Earth model is programmed with objects and classes, events over objects, properties and methods, the principles of OOP (polymorphism, encapsulation, inheritance), etc. are established for it [5].WLO and AE can be decomposed into many objects at one or another level of accuracy, each of which, in turn, decomposes into objects of a higher level of accuracy, etc. Each object changes its state in time, forming the so-called those or other *events*. The structure of the event in space images is shown in general in **Figure 13**: A, the earlier *actual state* of the object (or system of objects) O; B, the later real state; e, the *actual event* that transfers the state A of the object O to the state B; t, the moment of time (according to the "space" measures—the time interval with some average value); ti, the i-th reporting time; n, the number of reports; Bi, the *imaginary state* of the object O in the future with the known past state A; Ai, the imaginary state of the object O in the past at and the future state B; ai, the *imaginary event* of the object O in the future, taking the state A of the object O to the state Bi; bi, the imaginary event of the object O in the past, transferring the state Ai of the object O to the state B; and Ei, the latent state of the object

The "drive" of the state change A of the object is internal and/or external *factors* acting on the territory of the object. Internal factors operate from within, and it is difficult for them to identify the source of space images (favorable weather

#### *Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

*Lean Manufacturing and Six Sigma - Behind the Mask*

information obtained by deductive analysis, (5) general information obtained by image processing and deductive analysis, (6) recoverable information, (7) non-

*Image information: (a) information field (economic zone of the Timoshovo landfill, Noginsk district, Moscow* 

Deductive analysis is obtaining the maximum amount of information on a space image without the use of automated and automatic image processing algorithms. To obtain visible information, *reasoning* is not required, but *logical thinking* itself takes place in any case. For example, in order to *see* a house in the image, it is necessary to have different images of houses in the mind, in the limit—a full *spectrum of types* of houses ("manual" method of managed classification). We assume that information 3 and 4 do not include information 1: that something can be simply seen; it is not necessary to resort to additional costs. However, to see something on a

The reasoning behind deductive analysis has the following characteristics: (1) *Variability*—offers options for explaining a particular fact (details on the image). (2) *Distribution*—reasoning has a probabilistic and statistical character. (3) *Chain character*—one detail and one reasoning lead to another detail and another reasoning, etc. (4) *Detailing*—when interpreting one area of reasoning, they pass into its internal subdomain or conjugate domain. (5) *Algorithmization*—reasoning can be carried out on certain algorithms that allow to restore information. (6) *Schematization*—the system of reasoning is filled into some "vessel," i.e., takes the form of some model. Deductive analysis (recovery of the maximum amount of hidden information from the image through its detailed observation) is the development of conven-

Deductive analysis is variable—options are offered for explaining a particular fact (details on the image). Those reasoning have a probabilistic-statistical and a chain character, because one detail and one reasoning lead to another detail and

Processing of space images allows you to extract information hidden from the eyes. Human eyes are seen mainly in the visible spectrum, and information in the invisible spectrum is mostly hidden from the eyes. If a person had also seen in an invisible spectrum, he probably could have uncovered all the same information as when processing images but using only logical thinking (vision) and deductive analysis. But the processing would be required to speed up the extraction of infor-

Deductive analysis, for the most part, allows you to obtain information that cannot be obtained by modern image processing methods. We believe that this "extension" can be used to interpret visible images or images on which most of the objects can be distinguished. However, there is some general information obtained by both methods. The boundaries of deductive analysis end where the boundaries of image

recoverable information, and (8) all image information.

*region, Google Earth) and (b) types of information in the image.*

large number of images is less advisable than automating the process.

**66**

tional image surveillance.

**Figure 12.**

another reasoning and so on.

processing begin and vice versa.

mation from the images by means of automation.

*Information* can be visible or invisible and recoverable or non-recoverable. In the process of combining all the modern methods of image processing and *deduction* methods (and *induction*), some of the information on the image remains, in which it is impossible to extract for today—it is non-recoverable information. The limit of deductive analysis is the complete interpretation of the image, the possibility of explaining any details on the image in space and time.

Information field of the image is introduced: information sources (Si), information objects (O), informational AE of source (IAE), boundary of AE (C) of some radius (r), information signals from the sources to the objects (u), and internal (I) and external (II) objects of a source. The *source of information* is some object in the image, which is known for the most information; it can be seen and recognized. These objects are highlighted in the first step of the analysis. A lot of information sources form an information basis of the image—these are the reference objects of the image, to which all information is bound to the information field. The information is identified in the vicinity of the region S1S2…Sn, where n is the number of sources. Each source has a certain *neighborhood* (IAE). Internal objects relative to the source belong to its AE and have a *connection* with it; external objects are on the contrary. The boundary separates the internal objects from the external ones. The connection of the source Si to the object Oij is expressed in the presence of the information signal uij.

#### **3.3 Objects and events**

In the language of *object-oriented programming* (OOP), the Earth model is programmed with objects and classes, events over objects, properties and methods, the principles of OOP (polymorphism, encapsulation, inheritance), etc. are established for it [5].WLO and AE can be decomposed into many objects at one or another level of accuracy, each of which, in turn, decomposes into objects of a higher level of accuracy, etc. Each object changes its state in time, forming the so-called those or other *events*.

The structure of the event in space images is shown in general in **Figure 13**: A, the earlier *actual state* of the object (or system of objects) O; B, the later real state; e, the *actual event* that transfers the state A of the object O to the state B; t, the moment of time (according to the "space" measures—the time interval with some average value); ti, the i-th reporting time; n, the number of reports; Bi, the *imaginary state* of the object O in the future with the known past state A; Ai, the imaginary state of the object O in the past at and the future state B; ai, the *imaginary event* of the object O in the future, taking the state A of the object O to the state Bi; bi, the imaginary event of the object O in the past, transferring the state Ai of the object O to the state B; and Ei, the latent state of the object O for which there are no pictures, somehow identifying him.

The "drive" of the state change A of the object is internal and/or external *factors* acting on the territory of the object. Internal factors operate from within, and it is difficult for them to identify the source of space images (favorable weather

**Figure 13.** *Events and states on the time axis.*

conditions can lead to a thickening of the vegetation cover). External forces act from the outside, and for them a source (impact of a neighboring object) can be identified.

Two events have a *cause-consequence connection* (CCC) A⇒B, if one of them (A) is first before the other (B). If some "quantities" are known, the remaining ones can be calculated: the examples of the calculation schemes are shown in **Figure 14**, where A and B are known events; X, Y, and Z are unknown events; and a, b, x, y, and z are logical connections (known and unknown). In (a) for two known events A and B of object O on two cosmic images taken at different times, it is necessary to find an unknown CCC x that transferred A to B. At the same time, the design scheme can have more than one solution x. It is similar for the remaining examples of schemes. In scheme (b) from the known A, one must find the set of solutions {x, Y}, i.e., assume future events Y and the corresponding connections x. In the scheme (c), on the contrary, according to the known event B, it is necessary to restore the past (X, y).

The connection A⇒C⇒B forms a simple logical chain of three events A, B, and C (d–f). It is assumed there is one unknown intermediate event C that occurred chronologically between events A and B. It can be specified if the logical connection between A and B is not "felt" and a link is required. It is similar for more than one intermediate event.

On space images, an event is expressed in a change in the state of an object or system of objects, i.e., some territory. Knowing the two states, we can assume an event (event) that resulted from an earlier event in a later event. Thus the change in the state a⇒b of the object O in **Figure 16** is probably caused by the slippage of waste from the slope of the Timoshovo landfill site (Noginsk district of the Moscow region) into the water during the year. If the changes on the left side of the reservoir were due to the crushing of the reservoir, then it would be updated from other sides, which did not happen (on the right the contour of the shore line of the reservoir did not change). In addition, the slippage of waste into the reservoir according to Archimedes' law could not lead to a decrease in the water level; for this there would be other reasons, such as a prolonged absence of precipitation. Thus probably the physical meaning of changes in the texture of the reservoir on the left is the immersion of a part of the waste heap to the bottom of the reservoir.

The picture of events on the time interval [t1, t2] can be reconstructed, considering both the main variant of the flow and the less probable one. So, if the height of the landfill was large, the waste could spontaneously fall off the slope (e.g., under wind). But the height of this landfill is small; in addition, the area of the blade is large, i.e., more likely the deliberate littering of a natural object (pond). After the filling of the territory beyond the coastal line of the reservoir, some of the waste spontaneously falls into the reservoir, including to the bottom, leaving room for

#### **Figure 14.**

*Event (state) equations. The CCC model A*⇒*B, in which only A is the cause of B and only B is the consequence of A, differs from the real CCC in which there are background connections (***Figure 15***): A and B are events related to each other; C is external event-consequences A; R, external events-causes B; and a, b, and c, logical connections. "a and b" are "scattering" connections, for which the consequences of event A and the cause of event B are difficult to determine, or these consequences and causes are probabilistic. Estimating the probability of a logical connection between A and B by eye, p = M/N, where M is the number of logical connections that lead to B and N is the number of all logical connections flowing from A. Depending on the probability value, place such links as "only A led to B," "from A follows only B," "although A, but B," "if A, then B," etc.*

**69**

**Figure 16.**

*Event on the image (Google Earth).*

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

**Figure 15.**

overgrowing and disappearance as a habitat.

*The structure of the logical connection of real events.*

operation (some statement).

time, or cause-effect.

sequence of events.

tions, for example, spatial (**Figure 17**).

in the neighborhood of time (t < t1 and t > t2) can be restored.

new waste receipts. Under given conditions of survival, this reservoir is practically not suitable for complex life forms; proceeding from state b, one can assume its

For the possibility of *analyzing events* from images, including in the neighborhood of the interval [t1, t2], it is necessary to know at least two different states of the same territory. The more known states, the more accurate the picture of events. Outside the working interval, the construction of the picture of events has greater uncertainty than inside. The wider the neighborhood of the image, the more events

Marking objects on the workspace and asking them a lot of event-causes and event-effects (probable, since only part of the event-causes occurred, and eventeffects occur), the information picture is analyzed. Because objects and events "fight" on the same information field, it is necessary to establish links between them. The relationship can be analytically represented as the formula A o B, where A and B are objects or events, o is the operator (link), and A o B is the result of the

Links can be divided into *spatial*, *temporal*, and *logical*. Many of them are verbally given in the form of prepositions, prepositional words, and word combina-

attached to them (lawn, clutter, parking lot, access roads, outbuildings, entrances, etc.); the fences were installed "on" the parking lot after its asphalting (concreting). In some cases, communications may not be defined in space,

The time links are A "to" B, A "after" B, A "at one time with" B, "before A, B," etc. Temporary communications are established not only by the temporal gradation of the images but also by the basis of a single image over spatial relationships. For example, in **Figure 18**, buildings appeared before the objects

The spatial arrangement of objects in the image allows the image to be set in motion, i.e., restore its history and predict its future. Those on the spatial arrangement of objects, you can set events over these objects, as well as the

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

#### **Figure 15.**

*Lean Manufacturing and Six Sigma - Behind the Mask*

intermediate event.

conditions can lead to a thickening of the vegetation cover). External forces act from the outside, and for them a source (impact of a neighboring object) can be identified. Two events have a *cause-consequence connection* (CCC) A⇒B, if one of them (A) is first before the other (B). If some "quantities" are known, the remaining ones can be calculated: the examples of the calculation schemes are shown in **Figure 14**, where A and B are known events; X, Y, and Z are unknown events; and a, b, x, y, and z are logical connections (known and unknown). In (a) for two known events A and B of object O on two cosmic images taken at different times, it is necessary to find an unknown CCC x that transferred A to B. At the same time, the design scheme can have more than one solution x. It is similar for the remaining examples of schemes. In scheme (b) from the known A, one must find the set of solutions {x, Y}, i.e., assume future events Y and the corresponding connections x. In the scheme (c), on the contrary, according to the known event B, it is necessary to restore the past (X, y). The connection A⇒C⇒B forms a simple logical chain of three events A, B, and C (d–f). It is assumed there is one unknown intermediate event C that occurred chronologically between events A and B. It can be specified if the logical connection between A and B is not "felt" and a link is required. It is similar for more than one

On space images, an event is expressed in a change in the state of an object or system of objects, i.e., some territory. Knowing the two states, we can assume an event (event) that resulted from an earlier event in a later event. Thus the change in the state a⇒b of the object O in **Figure 16** is probably caused by the slippage of waste from the slope of the Timoshovo landfill site (Noginsk district of the Moscow region) into the water during the year. If the changes on the left side of the reservoir were due to the crushing of the reservoir, then it would be updated from other sides, which did not happen (on the right the contour of the shore line of the reservoir did not change). In addition, the slippage of waste into the reservoir according to Archimedes' law could not lead to a decrease in the water level; for this there would be other reasons, such as a prolonged absence of precipitation. Thus probably the physical meaning of changes in the texture of the reservoir on the left is the immersion of a part of the waste heap to the bottom of the reservoir.

The picture of events on the time interval [t1, t2] can be reconstructed, considering both the main variant of the flow and the less probable one. So, if the height of the landfill was large, the waste could spontaneously fall off the slope (e.g., under wind). But the height of this landfill is small; in addition, the area of the blade is large, i.e., more likely the deliberate littering of a natural object (pond). After the filling of the territory beyond the coastal line of the reservoir, some of the waste spontaneously falls into the reservoir, including to the bottom, leaving room for

*Event (state) equations. The CCC model A*⇒*B, in which only A is the cause of B and only B is the consequence of A, differs from the real CCC in which there are background connections (***Figure 15***): A and B are events related to each other; C is external event-consequences A; R, external events-causes B; and a, b, and c, logical connections. "a and b" are "scattering" connections, for which the consequences of event A and the cause of event B are difficult to determine, or these consequences and causes are probabilistic. Estimating the probability of a logical connection between A and B by eye, p = M/N, where M is the number of logical connections that lead to B and N is the number of all logical connections flowing from A. Depending on the probability value, place such links as "only A led to B," "from A follows only B," "although A, but B," "if A, then B," etc.*

**68**

**Figure 14.**

*The structure of the logical connection of real events.*

new waste receipts. Under given conditions of survival, this reservoir is practically not suitable for complex life forms; proceeding from state b, one can assume its overgrowing and disappearance as a habitat.

For the possibility of *analyzing events* from images, including in the neighborhood of the interval [t1, t2], it is necessary to know at least two different states of the same territory. The more known states, the more accurate the picture of events. Outside the working interval, the construction of the picture of events has greater uncertainty than inside. The wider the neighborhood of the image, the more events in the neighborhood of time (t < t1 and t > t2) can be restored.

Marking objects on the workspace and asking them a lot of event-causes and event-effects (probable, since only part of the event-causes occurred, and eventeffects occur), the information picture is analyzed. Because objects and events "fight" on the same information field, it is necessary to establish links between them.

The relationship can be analytically represented as the formula A o B, where A and B are objects or events, o is the operator (link), and A o B is the result of the operation (some statement).

Links can be divided into *spatial*, *temporal*, and *logical*. Many of them are verbally given in the form of prepositions, prepositional words, and word combinations, for example, spatial (**Figure 17**).

The time links are A "to" B, A "after" B, A "at one time with" B, "before A, B," etc. Temporary communications are established not only by the temporal gradation of the images but also by the basis of a single image over spatial relationships. For example, in **Figure 18**, buildings appeared before the objects attached to them (lawn, clutter, parking lot, access roads, outbuildings, entrances, etc.); the fences were installed "on" the parking lot after its asphalting (concreting). In some cases, communications may not be defined in space, time, or cause-effect.

The spatial arrangement of objects in the image allows the image to be set in motion, i.e., restore its history and predict its future. Those on the spatial arrangement of objects, you can set events over these objects, as well as the sequence of events.

**Figure 16.** *Event on the image (Google Earth).*

#### *Lean Manufacturing and Six Sigma - Behind the Mask*

#### **Figure 17.**

*Relationship of the objects and events: (a, c, d) the relationship of objects in space and (b, e) moving one object relative to another.*

#### **Figure 18.**

*Spatial relations of objects on the image (neighborhood of the building of the economic zone, Timoshovo landfill, Google Earth).*

Because logical connection implies a temporal, establishing the chronological state of objects, their individual *event-causes* and *event-consequences* can be "crossed" in pairs and distinguish among them plausible logical connections that can occur with one or another probability.

**71**

**Figure 19.**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

inverse B o A operations on the image.

the vicinity than man-made ones.

true (most probable), while others have a lower probability.

**3.4 Deductive analysis of images in Google Earth**

*Timoshovo landfill, and its surroundings, Elektrostal town (Google Earth).*

Each link has an inverse link to it, which is expressed through opposite prepositions such as "on" and "-incl.", "Above" and "-above" = "under", etc. *Opposite operations* correspond to "opposite" prepositions, for example, "above" and "under," "because of" and "from before," etc. Accordingly, we obtain straight lines A o B and

The object O is a section of the image that is different from its background, i.e., it can be associated with a set of *determinants*, concepts {Ii} i = 1…m, one of which is

From the point of view of images of an event (operations on objects), there are (1) the *appearance* and *disappearance* of an object, (2) growth and decrease of the object, (3) changing the site of the object, and (4) changing the state of the object. For specific types of objects, the type of event is confined to more specific manifestations of it, for example, "appearance"—growth (plants), building (building),

Let us give an "introduction" to the deductive analysis for a specific WLO—the Timoshovo landfill, the Elektrostal town, the Moscow region. You can conduct (1) at a different level of detail, (2) for a specific image, and (3) for a time series of images. This test site is one of the largest in the Moscow region and throughout the world. It is much larger than the Kuchino landfill and is located 4 km west of Elektrostal (**Figure 19**). In the first approximation, there are more natural areas in

The objects adjoin the landfill with parts of their borders: natural, large (in the southeast) and smaller (in the northwest) reservoirs; vegetation cover (forest and grass); anthropogenic, economic zone of the landfill in the west of the storage site; and road that fringes the landfill. In the vicinity of the landfill located settlements: cottage cooperative (in the southwest), the village Mechta (in the southeast).

The landfill has a fairly regular shape and a complex transport system installed on the active zone (in the Google Earth). The same overgrowing zone exists for a long time, so the "paths" overgrow on it. The outer part of the transport system is convenient for transport: the entrance to the landfill from three directions, i.e., from different settlements (sources of garbage), and a circumferential road giving access to the entry point (from the side of the economic zone) to the landfill from different directions, along and counterclockwise. From the point of view of visual detection, natural objects differ from anthropogenic ones in that they have an irregular shape—**Figure 20a** and **b**, whereas anthropogenic ones are correct

movement (car), etc. Each object is "capable" of its own group of events.

#### *Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

*Lean Manufacturing and Six Sigma - Behind the Mask*

**70**

**Figure 18.**

*landfill, Google Earth).*

**Figure 17.**

*relative to another.*

with one or another probability.

Because logical connection implies a temporal, establishing the chronological state of objects, their individual *event-causes* and *event-consequences* can be "crossed" in pairs and distinguish among them plausible logical connections that can occur

*Spatial relations of objects on the image (neighborhood of the building of the economic zone, Timoshovo* 

*Relationship of the objects and events: (a, c, d) the relationship of objects in space and (b, e) moving one object* 

Each link has an inverse link to it, which is expressed through opposite prepositions such as "on" and "-incl.", "Above" and "-above" = "under", etc. *Opposite operations* correspond to "opposite" prepositions, for example, "above" and "under," "because of" and "from before," etc. Accordingly, we obtain straight lines A o B and inverse B o A operations on the image.

The object O is a section of the image that is different from its background, i.e., it can be associated with a set of *determinants*, concepts {Ii} i = 1…m, one of which is true (most probable), while others have a lower probability.

From the point of view of images of an event (operations on objects), there are (1) the *appearance* and *disappearance* of an object, (2) growth and decrease of the object, (3) changing the site of the object, and (4) changing the state of the object. For specific types of objects, the type of event is confined to more specific manifestations of it, for example, "appearance"—growth (plants), building (building), movement (car), etc. Each object is "capable" of its own group of events.

### **3.4 Deductive analysis of images in Google Earth**

Let us give an "introduction" to the deductive analysis for a specific WLO—the Timoshovo landfill, the Elektrostal town, the Moscow region. You can conduct (1) at a different level of detail, (2) for a specific image, and (3) for a time series of images.

This test site is one of the largest in the Moscow region and throughout the world. It is much larger than the Kuchino landfill and is located 4 km west of Elektrostal (**Figure 19**). In the first approximation, there are more natural areas in the vicinity than man-made ones.

The objects adjoin the landfill with parts of their borders: natural, large (in the southeast) and smaller (in the northwest) reservoirs; vegetation cover (forest and grass); anthropogenic, economic zone of the landfill in the west of the storage site; and road that fringes the landfill. In the vicinity of the landfill located settlements: cottage cooperative (in the southwest), the village Mechta (in the southeast).

The landfill has a fairly regular shape and a complex transport system installed on the active zone (in the Google Earth). The same overgrowing zone exists for a long time, so the "paths" overgrow on it. The outer part of the transport system is convenient for transport: the entrance to the landfill from three directions, i.e., from different settlements (sources of garbage), and a circumferential road giving access to the entry point (from the side of the economic zone) to the landfill from different directions, along and counterclockwise. From the point of view of visual detection, natural objects differ from anthropogenic ones in that they have an irregular shape—**Figure 20a** and **b**, whereas anthropogenic ones are correct

**Figure 19.** *Timoshovo landfill, and its surroundings, Elektrostal town (Google Earth).*

**Figure 20.**

*Examples of objects: natural, (a) natural forest (internal forest) and (b) a natural water object; anthropogenic, (c) building and (d) pond (artificial pond) [Google Earth].*

(**Figure 20c** and **d**). Accordingly, the signs of natural and anthropogenic operations are reflected on the surface in the form of irregular and regular figures.

Consider a small "piece" of the vicinity of the landfill—**Figure 21a**.

We will give an assessment of how these or other details appeared on the image (in particular (1–8)) and in what order. It would seem that the site is simple enough and understandable (interpreted), but, in fact, the more you delve into its essence, the more questions arise, but more information can be "obtained" from the site. Indeed, everything and every detail in the image, in particular, has its own *causes*, *signs*, and *consequences*. If you pay attention to a specific image of the Earth's surface and mentally go over all its details, you can understand how many causes and consequences are on the image, and they all connect with each other in a complex system of cause-effect relationships hidden from the eyes. "There" can only be penetrated by reasoning.

For convenience, let us imagine deductive analysis schematically. Because lines and structures of reasoning are many, at least part should be reduced to a certain table. The diagram of the analysis of a pair of pictures is made differently; one of the variants is **Table 1**. The table shows the scheme for a *chronological pair*: two objects 1 and 2, one of which appeared before the other (1 before 2—straight pair, 2 before 1—reverse). The columns are added to the table: "arguments for" and "arguments against" the corresponding chronological sequence.

**Figure 21b** comments on some points in **Table 1**: (1) the epicenter of the group of trees (early trees), (2 and 3) the directions of the group's growth from the epicenter (the trees grow later), (4–6) the epicenter and the direction of growth (trees grow simultaneously), and (7) elementary trees (grow after 1). Different types of growth of trees on the slope also have their own causes and are due to the features of the soil, the illumination (8), the same slope angle (9), the soil state (10), etc.

The processing of a large amount of information based on chronopairs was carried out, including at a deeper level of chronopairs 1⇔2.

One of the assumptions is that on both sides of the road, the plantation formed in the process of its design—from the field—exists now; from the landfill it has disappeared when the landfill has grown but has grown on its slopes. This is due to

**73**

**Figure 22.** *Chronological chain.*

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

conditions, properties of the soil structure and its relief).

**The direct order (1**⇒**2)**

**The inverse order (2**⇒**1)**

**Table 1.**

*Chronological pair (1, 2).*

the fact that the landfill could not exist without a road (**Figure 21b**), i.e., the road was created before the landfill, and in its place was something else—for example, the continuation of field 5, which was cut off by the road and, in the future, replaced by a testing range. It was a field (an artificial object), not a meadow (natural), because the forest under it was cut along the right lines 6, and in some places the forest grew over the edges and took a less correct form (e.g., line 7). But the agricultural field could not be so small. It turns out that the landfill was formed in an environmentally friendly place. Before the agricultural field, there were meadows, there was more forest, and there were probably water bodies, because on the edges of the landfill, there are many small and cut ponds, as well as elements of the water system regulation (dams, canals, dams, etc.). Accordingly, all elements of the landfill, including vegetation on its slope 8, a path along its perimeter 9, arose after its formation.

parallel to the road) and at the base (random distribution of forest area elements).

Trees are not elements of road design, because on visible signs are formed by growth and form the wrong (natural) form. Before the design of the road, the trees occupied a larger area than at the time of the survey, but some of them were cut down in the course of the land works for designing the road and the landfill. However, over time, the area of growth expands, and on the slope their age and growth rate are lower than on flat terrain, since on the slope, they began to grow after its formation arbitrarily, whereas at the base of the landfill the trees were not removed and grew simultaneously with the development of the landfill. In addition, the growth rate of trees on a slope is on average lower than on flat terrain (due to the difference in light

Trees are elements of road design, acting as protective screens, just as a body of water is an accompanying element of road design and accumulation of leachate from a landfill, assuming the correct shape. The rate of their growth at the base is lower than on the slope due to the fact that soil pollution by the filtration waters of the landfill spreads more at the base and level terrain than on the slope. Before designing the road, the trees formed an "island" among the field, but with the formation of a landfill and then girdling the road, the main part of the field was cut. This explains the different nature of the growth of trees on the slope (forest belt

The chronology of events (month and year) can be assumed based on a series of events, known times of occurrence (e.g., of dumps), the size and density of trees,

Thus a certain *chronological chain* of formation of objects is built, which can be represented in the form of a scheme with the designation of the main arguments of

the correctness of their shaping (e.g., boundaries), etc.

*chronological links* (one visual argument)—**Figure 22**.

**Figure 21.** *Analyzed region: (a) the section of visual detection and (b) feature sites (Google Earth).*

### **The direct order (1**⇒**2)**

*Lean Manufacturing and Six Sigma - Behind the Mask*

**Figure 20.**

(**Figure 20c** and **d**). Accordingly, the signs of natural and anthropogenic operations

We will give an assessment of how these or other details appeared on the image (in particular (1–8)) and in what order. It would seem that the site is simple enough and understandable (interpreted), but, in fact, the more you delve into its essence, the more questions arise, but more information can be "obtained" from the site. Indeed, everything and every detail in the image, in particular, has its own *causes*, *signs*, and *consequences*. If you pay attention to a specific image of the Earth's surface and mentally go over all its details, you can understand how many causes and consequences are on the image, and they all connect with each other in a complex system of cause-effect relationships hidden from the eyes. "There" can only be penetrated by reasoning. For convenience, let us imagine deductive analysis schematically. Because lines and structures of reasoning are many, at least part should be reduced to a certain table. The diagram of the analysis of a pair of pictures is made differently; one of the variants is **Table 1**. The table shows the scheme for a *chronological pair*: two objects 1 and 2, one of which appeared before the other (1 before 2—straight pair, 2 before 1—reverse). The columns are added to the table: "arguments for" and "argu-

**Figure 21b** comments on some points in **Table 1**: (1) the epicenter of the group of trees (early trees), (2 and 3) the directions of the group's growth from the epicenter (the trees grow later), (4–6) the epicenter and the direction of growth (trees grow simultaneously), and (7) elementary trees (grow after 1). Different types of growth of trees on the slope also have their own causes and are due to the features of the soil, the illumination (8), the same slope angle (9), the soil state (10), etc.

The processing of a large amount of information based on chronopairs was car-

One of the assumptions is that on both sides of the road, the plantation formed in the process of its design—from the field—exists now; from the landfill it has disappeared when the landfill has grown but has grown on its slopes. This is due to

are reflected on the surface in the form of irregular and regular figures. Consider a small "piece" of the vicinity of the landfill—**Figure 21a**.

*Examples of objects: natural, (a) natural forest (internal forest) and (b) a natural water object;* 

*anthropogenic, (c) building and (d) pond (artificial pond) [Google Earth].*

ments against" the corresponding chronological sequence.

ried out, including at a deeper level of chronopairs 1⇔2.

**72**

**Figure 21.**

*Analyzed region: (a) the section of visual detection and (b) feature sites (Google Earth).*

Trees are not elements of road design, because on visible signs are formed by growth and form the wrong (natural) form. Before the design of the road, the trees occupied a larger area than at the time of the survey, but some of them were cut down in the course of the land works for designing the road and the landfill. However, over time, the area of growth expands, and on the slope their age and growth rate are lower than on flat terrain, since on the slope, they began to grow after its formation arbitrarily, whereas at the base of the landfill the trees were not removed and grew simultaneously with the development of the landfill. In addition, the growth rate of trees on a slope is on average lower than on flat terrain (due to the difference in light conditions, properties of the soil structure and its relief).

#### **The inverse order (2**⇒**1)**

Trees are elements of road design, acting as protective screens, just as a body of water is an accompanying element of road design and accumulation of leachate from a landfill, assuming the correct shape. The rate of their growth at the base is lower than on the slope due to the fact that soil pollution by the filtration waters of the landfill spreads more at the base and level terrain than on the slope. Before designing the road, the trees formed an "island" among the field, but with the formation of a landfill and then girdling the road, the main part of the field was cut. This explains the different nature of the growth of trees on the slope (forest belt parallel to the road) and at the base (random distribution of forest area elements).

#### **Table 1.**

*Chronological pair (1, 2).*

the fact that the landfill could not exist without a road (**Figure 21b**), i.e., the road was created before the landfill, and in its place was something else—for example, the continuation of field 5, which was cut off by the road and, in the future, replaced by a testing range. It was a field (an artificial object), not a meadow (natural), because the forest under it was cut along the right lines 6, and in some places the forest grew over the edges and took a less correct form (e.g., line 7). But the agricultural field could not be so small. It turns out that the landfill was formed in an environmentally friendly place. Before the agricultural field, there were meadows, there was more forest, and there were probably water bodies, because on the edges of the landfill, there are many small and cut ponds, as well as elements of the water system regulation (dams, canals, dams, etc.). Accordingly, all elements of the landfill, including vegetation on its slope 8, a path along its perimeter 9, arose after its formation.

The chronology of events (month and year) can be assumed based on a series of events, known times of occurrence (e.g., of dumps), the size and density of trees, the correctness of their shaping (e.g., boundaries), etc.

Thus a certain *chronological chain* of formation of objects is built, which can be represented in the form of a scheme with the designation of the main arguments of *chronological links* (one visual argument)—**Figure 22**.

**Figure 22.** *Chronological chain.*


**Table 2.** *Probabilistic scheme.*

General arguments are given only for a specific variant of the *chain of events*. Theoretically, there may be other chains in which the appearance sequences of objects will be different. But in many cases the reasoning will be much more complicated, i.e., for a chronological pair, much more reasoning is required.

In deductive analysis, you can use many other algorithms and schemes, such as the *probability scheme* (**Table 2**). It shows (1) the formalization of the probability of "eye" of any of the identifications of the object 3 in **Figure 21a** and (2) the events logically associated with the event of felling trees (6, 7). If a complete group of n events (assertions) is given, then the probabilities pi of this events are reduced to probabilities qi, the sum of which is 1: ∑*i*=1 *<sup>n</sup> qi* <sup>=</sup> 1,*qi* <sup>=</sup> *pi* \_\_ *<sup>s</sup>* ,*s* = ∑*i*=1 *<sup>n</sup> pi*.

### **4. Conclusion**

The solution of the problem of littering will belong to more than one generation of humanity, as its relevance will only grow with time. But it is possible to begin the solution of this prolonged emergency situation right now by setting a point of support inside (i.e., changing the inner world, consciousness) and outside (i.e., changing the external world, i.e., the environment around us).

Internal change is purely individual, and the external one can be given a logical explanation. The second, in particular, includes the monitoring of the WLO with a certain power impulse (at the physical, economic, social levels).

### **Author details**

Andrey Alexandrovich Richter Department of Operation Space Monitoring, State Scientific Institution "Institute for Scientific Research of Aerospace Monitoring "AEROCOSMOS"", Zheleznodorozhny (Moscow region), Russia

\*Address all correspondence to: urfin17@yandex.ru

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**75**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

[1] Design instructions, exploitation and reclamation solid waste landfills [Electronic resource]: Agreed letter of the State Committee sanitary epidemiological control of the Russian Federation from June 10, 1996 № 01-8/17-11 (approved. Mistroem Russia November 2, 1996). Not published Access from sprav. ConsultantPlus

[2] Google Earth. Electronic resource. US, 2005-2017. Available from: https:// www.google.com/intl/ru/earth/

[3] Yandex maps. Electronic resource. RF. 2017. Available from: https://yandex.ru

[4] Google maps. Electronic resource. US 2017. Available from: https://www.

[5] Meyer B. The Basics of Object oriented programming: Studies.

manual/Bertrand Meyer. Know"Intuit".

google.com/maps

2016. 970

systems

**References**

*Some Aspects of Visual Detection of Dumps DOI: http://dx.doi.org/10.5772/intechopen.81726*

## **References**

*Lean Manufacturing and Six Sigma - Behind the Mask*

**74**

**Author details**

**4. Conclusion**

**Table 2.**

*Probabilistic scheme.*

Andrey Alexandrovich Richter

provided the original work is properly cited.

Zheleznodorozhny (Moscow region), Russia

probabilities qi, the sum of which is 1: ∑*i*=1

\*Address all correspondence to: urfin17@yandex.ru

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

General arguments are given only for a specific variant of the *chain of events*. Theoretically, there may be other chains in which the appearance sequences of objects will be different. But in many cases the reasoning will be much more com-

4 40 Rattle, moat 4 5 Cutting out sick trees

**Object identification Connection of events**

1 80 Water object 1 70 Formation of the agricultural field 2 10 Shadow 2 5 Carrying out the road 3 5 Forest mass 3 20 Expanding the boundaries of the

**i pi Statement j pj Statement**

In deductive analysis, you can use many other algorithms and schemes, such as the *probability scheme* (**Table 2**). It shows (1) the formalization of the probability of "eye" of any of the identifications of the object 3 in **Figure 21a** and (2) the events logically associated with the event of felling trees (6, 7). If a complete group of n events (assertions) is given, then the probabilities pi of this events are reduced to

*<sup>n</sup> qi* <sup>=</sup> 1,*qi* <sup>=</sup> *pi* \_\_

The solution of the problem of littering will belong to more than one generation of humanity, as its relevance will only grow with time. But it is possible to begin the solution of this prolonged emergency situation right now by setting a point of support inside (i.e., changing the inner world, consciousness) and outside (i.e.,

Internal change is purely individual, and the external one can be given a logical explanation. The second, in particular, includes the monitoring of the WLO with a

*<sup>s</sup>* ,*s* = ∑*i*=1

*<sup>n</sup> pi*.

landfill

plicated, i.e., for a chronological pair, much more reasoning is required.

Department of Operation Space Monitoring, State Scientific Institution "Institute for Scientific Research of Aerospace Monitoring "AEROCOSMOS"",

changing the external world, i.e., the environment around us).

certain power impulse (at the physical, economic, social levels).

[1] Design instructions, exploitation and reclamation solid waste landfills [Electronic resource]: Agreed letter of the State Committee sanitary epidemiological control of the Russian Federation from June 10, 1996 № 01-8/17-11 (approved. Mistroem Russia November 2, 1996). Not published Access from sprav. ConsultantPlus systems

[2] Google Earth. Electronic resource. US, 2005-2017. Available from: https:// www.google.com/intl/ru/earth/

[3] Yandex maps. Electronic resource. RF. 2017. Available from: https://yandex.ru

[4] Google maps. Electronic resource. US 2017. Available from: https://www. google.com/maps

[5] Meyer B. The Basics of Object oriented programming: Studies. manual/Bertrand Meyer. Know"Intuit". 2016. 970

**77**

**Chapter 6**

**Abstract**

big data analytics

Drive Better

Services Six Sigma: Knowing the

The challenges in lean Six Sigma implementation start from terminology to applicability to actual application and finally in terms of experiencing the change. Six Sigma projects are being used as an event response antidote rather than as a culture in organizations. Could there be a debate on your "X sigma" versus my "Y sigma"? Should lean practice be the front end or the back end or somewhere in the middle embedded in the Breakthrough Strategy has been a matter of debate among practitioners for many years now. Ego centric debates, a reason to justify failures, a failure to identify the purpose are contributors to the dilemma. Historically, the genesis of Six Sigma carries a setting of manufacturing yards, so should that be a reason to brand it as unsuitable for services, or is there a need to "dilute" the rigor in methodology or search for alternative techniques to facilitate application in a pure services context? Now, in an era of Industry 4.0 and Big Data Analytics, does Six Sigma continue to have a relevance? Should machine learning algorithms remain in the ever evolving list of tools and techniques within the Six Sigma book of knowledge? This chapter aims to address the above questions and more number of questions that we

experience on a day-to-day basis in Six Sigma applications in the real world.

**1. Introduction to TQM and lean Six Sigma evolution**

**Keywords:** business excellence, lean Six Sigma, breakthrough strategy, industry 4.0,

**Chapter learning objectives:** understanding of evolution of TQM, lean, Six Sigma in the industry, application issues in services sector, financial and overall evaluation of application, failure modes & critical success factors, emerging trends in application.

Tracing the history of quality journey up to the age of total quality management, it was a period of promises such as enterprises being strongly committed to customers and their problems being of utmost priority for the senior management. People of the firm realize that they are there because of the customers, hence it becomes imperative that customer problems are be resolved. Also ways and means to be found out to make sure, problems do not recur. But, the obvious fact is assurances never satisfy a professional management, unless tangible achievements are showcased. Thus, managers slowly started withdrawing any long term support to such total quality management initiatives as they found nothing that contributes directly

Debates and Failure Modes to

*Sajit Jacob and Krishnamurthy Kothandaraman*

### **Chapter 6**
