**2.3 Intelligent quality control systems**

The concept of Intelligent Quality Control Systems (IQCS) or Smart quality control systems (SQCS) is founded on the premise that, in Smart Manufacturing production, quality control (QC), is driven by the infusion of Big Data Analytics, Artificial Intelligence (AI), Cyber-Physical Systems (CPS), Robotics and intensity of Human-to-Machine (H2M) interactions. The concept replaces the traditional QC systems in the manufacturing processes, as automation take over most of the operations or tasks that were routine tasks performed by human. Smart quality control is mainly executed to physically manage various Smart machines or tools through a cloud enabled platform. These technologies are capable of communicating both with the products (Smart products) and their environments. They are capable of detecting any slight defects and delays that could hamper manufacturing processes, and then communicate the same to the shopfloor, using fitted sensors [22, 25]. These gadgets work autonomously to create seamless communication between themselves. For example, [21, 26] installed sensors, utilised simulation and AI techniques assist in design and implementation of automatic machine model that predicts machine health status, which in turn can diagnoses any quality defects that could results from the machining failures. This result in a cost-effective solution in monitoring the production process to improve the quality of the products based on Industry 4.0 technologies.

Therefore, QC in Smart Manufacturing or Industry 4.0 revolution seem to take a different route as Industry 4.0 revolution is envisaged to leverage on a holistic automation, business information, and manufacturing execution architecture to improve industry with integration of all aspects of production and commerce across company boundaries for greater efficiency [27]. Industry 4.0 revolution is a complete departure from past three predecessors in several ways. First and foremost, Industry 4.0 revolution has come with Smart factories, Industrial Internet of Things, Smart Manufacturing, and Advanced Manufacturing, which were not experienced or witnessed in the past three successive Industrial revolutions. Second, Industry 4.0 revolution workplace emphasises so much on the Smart workers, Cyber Physical and Robotics in all the sphere of its Manufacturing and Industrial operations. The Internet of Things (Smart manufacturing, Additive Manufacturing, AI) have transformed the traditional production process of assembly lines with the introduction of asynchronous systems where predetermined workflows based on production work orders are running enterprise business systems [27]. Hence, making production steps that are centrally in communication to each Manufacturing station, which is harmonised with the assembly line.

In contrast, asynchronous manufacturing is based on I4.0 revolution concept in which components in the production flow using auto-identification technology to inform each machine and operator on what needs to be done to produce customised end product. This activity takes place at each step of the production process. In this process, the machines are more flexible, which make them adaptable to the requirements for the part being made at each production steps. This entire concept is a product of Industry 4.0 revolution. The systems assist in achieving a highly flexible, lean, and agile production process that allow for a variety of distinctive products to be produced in the same production facility. The process is based on the premise of profitable mass customisation that enables the production of small lots (even as small as single unique item). This is due to the ability to rapidly configure machines to adapt to customer-supplied specifications and additive manufacturing [27]. **Figure 2** below gives a snapshot of Manufacturing production process and the quality control under Smart Manufacturing. Inputs- denotes Smart raw materials, and Smart workers that are capable to communicating with Robotics to execute the tasks. Such systems comprise production facilities, storage systems and smart machines which trigger actions, exchange information complete autonomously and are able to control each other independently [8, 28].

Smart raw materials will be detected by machines without necessarily having to be verified or inspected as the case in the past. The machines fitted with sensors will be able to differentiate between quality inputs (Smart raw materials) and defects, if possible reworked, or discarded all together, a thing that was formerly done by human beings in the traditional manufacturing set up (see, **Figure 2**). Inputs will have Smart workers, who are capable of interacting with computers and Robots. The Smart Manufacturing is fully equipped with actors, sensors and CPS where

**25**

and extensive data analysis [25].

*Smart Manufacturing: Quality Control Perspectives DOI: http://dx.doi.org/10.5772/intechopen.95143*

as in a social network" [8, 28] as shown in **Figure 2**.

"human beings, machines and resources communicate with each other as naturally

or are detected, the machines can be adjusted in real time accordingly.

In **Figure 2**, Smart Manufacturing process begins with the input as smart material (because these materials are fitted with microchips, sensors), which enable them to be recognised and detected by the intelligent machines. The fact is, the material can be configured or reconfigured according to the Smart Manufacturing requirements, if found not to meet the specific product manufacturing specifications, then it can be discarded or reworked. This allows for the smooth flow of manufacturing process. This results in an improved finished product quality and reduced level of production errors [5, 25]. The implementation in the technology production process namely, ICTs, sensors technology and robotic technology, have the ability to record the production process in each element (instead of sampling and control) and detecting errors that occur during the process [25]. If errors occur

In the manufacturing process, there are Smart machining, Smart monitoring, Smart control, and Scheduling (**Figure 2**). Cyber-Physical Systems enable Smart machine tools to capture the real-time data and send it to a cloud-based central system so that machine tools and their twined services could be synchronised to provide to Smart Manufacturing solutions. While, Smart monitoring, monitors the operations, maintenance, and optimal scheduling of manufacturing systems. Smart monitoring assist in Smart Manufacturing by giving warnings/alerts if some abnormality occurs to machines/tools. In addition, Smart control, though can be executed to physically manage various smart machines or robot through Cloud enabled platform [5] but do allow the end-users to switch off a machine or robot via their Smartphones [29]. This allows the decisions to be reflected in frontline manufacturing sites such as robot-based assembly lines or Smart machines (**Figure 2**). Then finally, Smart scheduling which includes advanced models and algorithms draw on data captured from sensors [5]. These data-driven techniques and advanced decision architecture is used in smart scheduling. **Figure 2**, with the assistance of data input mechanisms, the output resolutions are fed back to the parties through various means (feed loop) [5, 30]. **Figure 2** for example, comprises Big Data, Clouding Computing, Internet, Simulation, Artificial Intelligence, and System Integration, which represent technologies, such as Additive Manufacturing, Autonomous Machines, and Human -to-Man (H2M) integration. These produce faster, stronger and more consistent than workers with a combination of new sensors and actuators

In **Figure 2** above, process represents transformation process of Smart raw materials into final products. Industry 4.0 revolution comprises a high-resolution, adaptive production control (APC) such as Smart Control that can be achieved through development of Cyber-Physical production control systems [10]. In addition, Smart control is mainly executed to physically manage various Smart machines or tools through a cloud enabled platform [31]. End-users (Smart customers are able to get a smart product, which are tailored-made according to their personalised needs. In addition, smart customers are able to interact with smart products from smart manufacturing and could easily identify with such products. And if the product fails to meet their specifications [29], the decisions could then be timely reflected in frontline manufacturing sites such as robot-based assembly lines or smart machines [32], as shown in **Figure 2** above. For instance, the Smart quality control in Smart Manufacturing is well illustrated by Changying Precision Technology Company's factory in Dongguan city. This is the first unmanned factory run by computercontrolled robots, numerical control machining equipment, unmanned transport trucks, and automated warehouse equipment. It is said that about six hundred human assembly-line workers were replaced with this automation alone. The result

**Figure 2.** *Intelligent quality control Systems in Smart Manufacturing. Source: Author's own illustration.*

#### *Smart Manufacturing: Quality Control Perspectives DOI: http://dx.doi.org/10.5772/intechopen.95143*

*Quality Control - Intelligent Manufacturing, Robust Design and Charts*

station, which is harmonised with the assembly line.

are able to control each other independently [8, 28].

Therefore, QC in Smart Manufacturing or Industry 4.0 revolution seem to take a different route as Industry 4.0 revolution is envisaged to leverage on a holistic automation, business information, and manufacturing execution architecture to improve industry with integration of all aspects of production and commerce across company boundaries for greater efficiency [27]. Industry 4.0 revolution is a complete departure from past three predecessors in several ways. First and foremost, Industry 4.0 revolution has come with Smart factories, Industrial Internet of Things, Smart Manufacturing, and Advanced Manufacturing, which were not experienced or witnessed in the past three successive Industrial revolutions. Second, Industry 4.0 revolution workplace emphasises so much on the Smart workers, Cyber Physical and Robotics in all the sphere of its Manufacturing and Industrial operations. The Internet of Things (Smart manufacturing, Additive Manufacturing, AI) have transformed the traditional production process of assembly lines with the introduction of asynchronous systems where predetermined workflows based on production work orders are running enterprise business systems [27]. Hence, making production steps that are centrally in communication to each Manufacturing

In contrast, asynchronous manufacturing is based on I4.0 revolution concept in which components in the production flow using auto-identification technology to inform each machine and operator on what needs to be done to produce customised end product. This activity takes place at each step of the production process. In this process, the machines are more flexible, which make them adaptable to the requirements for the part being made at each production steps. This entire concept is a product of Industry 4.0 revolution. The systems assist in achieving a highly flexible, lean, and agile production process that allow for a variety of distinctive products to be produced in the same production facility. The process is based on the premise of profitable mass customisation that enables the production of small lots (even as small as single unique item). This is due to the ability to rapidly configure machines to adapt to customer-supplied specifications and additive manufacturing [27]. **Figure 2** below gives a snapshot of Manufacturing production process and the quality control under Smart Manufacturing. Inputs- denotes Smart raw materials, and Smart workers that are capable to communicating with Robotics to execute the tasks. Such systems comprise production facilities, storage systems and smart machines which trigger actions, exchange information complete autonomously and

Smart raw materials will be detected by machines without necessarily having to be verified or inspected as the case in the past. The machines fitted with sensors will be able to differentiate between quality inputs (Smart raw materials) and defects, if possible reworked, or discarded all together, a thing that was formerly done by human beings in the traditional manufacturing set up (see, **Figure 2**). Inputs will have Smart workers, who are capable of interacting with computers and Robots. The Smart Manufacturing is fully equipped with actors, sensors and CPS where

*Intelligent quality control Systems in Smart Manufacturing. Source: Author's own illustration.*

**24**

**Figure 2.**

"human beings, machines and resources communicate with each other as naturally as in a social network" [8, 28] as shown in **Figure 2**.

In **Figure 2**, Smart Manufacturing process begins with the input as smart material (because these materials are fitted with microchips, sensors), which enable them to be recognised and detected by the intelligent machines. The fact is, the material can be configured or reconfigured according to the Smart Manufacturing requirements, if found not to meet the specific product manufacturing specifications, then it can be discarded or reworked. This allows for the smooth flow of manufacturing process. This results in an improved finished product quality and reduced level of production errors [5, 25]. The implementation in the technology production process namely, ICTs, sensors technology and robotic technology, have the ability to record the production process in each element (instead of sampling and control) and detecting errors that occur during the process [25]. If errors occur or are detected, the machines can be adjusted in real time accordingly.

In the manufacturing process, there are Smart machining, Smart monitoring, Smart control, and Scheduling (**Figure 2**). Cyber-Physical Systems enable Smart machine tools to capture the real-time data and send it to a cloud-based central system so that machine tools and their twined services could be synchronised to provide to Smart Manufacturing solutions. While, Smart monitoring, monitors the operations, maintenance, and optimal scheduling of manufacturing systems. Smart monitoring assist in Smart Manufacturing by giving warnings/alerts if some abnormality occurs to machines/tools. In addition, Smart control, though can be executed to physically manage various smart machines or robot through Cloud enabled platform [5] but do allow the end-users to switch off a machine or robot via their Smartphones [29]. This allows the decisions to be reflected in frontline manufacturing sites such as robot-based assembly lines or Smart machines (**Figure 2**). Then finally, Smart scheduling which includes advanced models and algorithms draw on data captured from sensors [5]. These data-driven techniques and advanced decision architecture is used in smart scheduling. **Figure 2**, with the assistance of data input mechanisms, the output resolutions are fed back to the parties through various means (feed loop) [5, 30]. **Figure 2** for example, comprises Big Data, Clouding Computing, Internet, Simulation, Artificial Intelligence, and System Integration, which represent technologies, such as Additive Manufacturing, Autonomous Machines, and Human -to-Man (H2M) integration. These produce faster, stronger and more consistent than workers with a combination of new sensors and actuators and extensive data analysis [25].

In **Figure 2** above, process represents transformation process of Smart raw materials into final products. Industry 4.0 revolution comprises a high-resolution, adaptive production control (APC) such as Smart Control that can be achieved through development of Cyber-Physical production control systems [10]. In addition, Smart control is mainly executed to physically manage various Smart machines or tools through a cloud enabled platform [31]. End-users (Smart customers are able to get a smart product, which are tailored-made according to their personalised needs. In addition, smart customers are able to interact with smart products from smart manufacturing and could easily identify with such products. And if the product fails to meet their specifications [29], the decisions could then be timely reflected in frontline manufacturing sites such as robot-based assembly lines or smart machines [32], as shown in **Figure 2** above. For instance, the Smart quality control in Smart Manufacturing is well illustrated by Changying Precision Technology Company's factory in Dongguan city. This is the first unmanned factory run by computercontrolled robots, numerical control machining equipment, unmanned transport trucks, and automated warehouse equipment. It is said that about six hundred human assembly-line workers were replaced with this automation alone. The result

was a fivefold reduction in manufacturing errors and an increase in production of more than 250 percent [27, 33]. This is a typical example of how quality control (QC) in Smart Manufacturing has been operationalised.

Smart Manufacturing or Industry 4.0 revolution is built around the concept of self-control or managing production processes requires open software and communications standards that allow sensors, controllers, people, machines, equipment, logistics systems, and products to communicate and cooperate with each other directly [5, 27]. This simply means the use of human beings in the manufacturing process particularly in the production/manufacturing processes as quality control inspectors, is minimised, if not eliminated. However, to embrace Smart Manufacturing in sustainable way, require that Manufacturing industries adopt technologies transformations with training and development programmes in order to fit their workforce with the new workplace requirements, such as new tools and technologies [11, 34]. This will ensure that gaps in skills and knowledge created by the Smart Manufacturing technologies do not have serious impacts on the workforce work life. Therefore, the implementation of Smart Quality Control Systems (SQCS) or Intelligent Quality Control Systems (IQCS) in Industry 4.0 requires further employee skills and competencies, such as ICT know-how, interdisciplinary competencies and special personality traits [34, 35]. This is because Human-to-Machine (H2M) collaboration that is necessary as some production tasks are too unstructured to be fully automatised.

In the production assembly/manufacturing assembly, Virtual Reality (VR) and operator create 'cognitive interaction'. For example, VR technology provides a combination of interactive reality and advanced simulations that can replicate a design, assembly, or manufacturing environment and allow the smart operator to interact with any (Machine tools, production line, hand-tool, a robot, a factory), with reduced risk and real time feedback as shown in **Figure 2** [11]. In addition, VR, at product assembly stage, CAD models of parts, hand tools, and assemblies can be transformed into interactive simulations (assembly sequence). This can be used in the training of operators working in a complex assembly tasks, and at product manufacturing stage. [11] opine that VR brings to life the "virtual factory" as an integrated simulation model of the major subsystems of a factory layout (such as arrangements of machinery, equipment and inventories for smooth flow of work, material and finished products). These arrangements form continuous communication between humans to machines and products during the production process. This is enabled by Cyber-Physical Production Systems (CPPS) in order to execute its tasks. The overall aim is to decrease cost, time efficiency, and improve product quality, which requires a broad understanding of the enabling technologies as well as methods and tools [13].

Products in Smart Manufacturing are 'Smart', with embedded sensorics that is used via wireless network for real-time data collection for localisation, for measuring product state and environment conditions [9]. In **Figure 2**, Smart products have control and processing capabilities, thus control their logistical path through the production and even optimise the production workflow. In addition, Smart products are capable of monitoring their own state during the whole lifecycle, including their lifetime or application [9].

Already in use is the intelligent Quality Control Systems (IQCS), which has replaced the traditional QC in the manufacturing processes. In Smart Manufacturing, all aspects pertaining to products quality control are first defined. In the first step, the technical requirements for the quality control system in development are defined and documented. In addition, the final document is intended for as a working-document supporting the requirements process during the development of the quality control systems [13]. The introduction of intelligent-based

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*Smart Manufacturing: Quality Control Perspectives DOI: http://dx.doi.org/10.5772/intechopen.95143*

of the overall value chain (see **Figure 2**).

**2.4 Benefits of intelligent quality control systems**

improving the quality of work [9, 11].

way [9, 22, 36].

possible [9, 36].

reduced.

**3. Summary**

quality control necessitates integration steps within and outside the manufacturing industry. It affects sensors and actuators as well as general manufacturing processes, like information and documentation flows. Furthermore, manufacturing partners or customers have to be integrated into the development as they are all part

IQCS brings with it several benefits to those organisations that will be able to adapt the new technologies in Smart Manufacturing processes compared to traditional quality control has been part of the manufacturing processes in the previous

• "Time to market" to develop, produce and market new products and services, requiring higher and faster innovation capability [36]. This is due to the cutting-edge technologies such Additive manufacturing, Industrial Internet of Things (IIoTs), Augmented Reality and Virtual Reality. These have eliminated wastes that were formerly associated with human errors hence creating lean production of products that are competitive globally. Augmented Reality (AR) assist in reducing defects, rework and redundant inspection by offering intuitive information and combining operator intelligence and flexibility with error-proofing systems to increase efficiency of manual work steps, while

• Increased "customisation" to satisfy individual consumer demands, in a buyer' market, not anymore a seller's one, leading to higher product individualisation; meaning products may not need to be produced in mass as before, because the manufacturers will be able to produce very small series (single product if needed). This technology provides fast configuration of machines and produc-

• Higher "flexibility" with faster and more versatile production processes able to produce smaller lot quantities with high quality and a cost-effective

• "Decentralised" decision making with fewer organisational hierarchies be

• Increased resource "efficiency" by using more efficient and closed loops, regenerative, and restorative physical and economic cycles, where products and raw materials retain their physical characteristics and value as much as

Quality control (QC) has evolved from the Middle Ages to the present time, with

the changes in manufacturing industries. As industrial revolutions transformed itself, so is the QC systems. First QC started as '*caveat emptor'*, whereby the control was entirely in the hands of Artisan, and it was the responsibility of the customer to ensure that the product is of quality. This was followed by punitive measures imposed on the Artisan who produces inferior products. From there came the '*operator quality control'* (OQC). The operator was to ensure that a product meet

tion process, as well as their adaptation to customer requirement [25].

three industrial revolutions. Such benefits are summarised as follows:
