**1. Introduction**

Quality control issue is one of the cardinal factors in product manufacturing. It entails profiling areas where quality is to be maintained and enforced. In manufacturing parlance, quality could be described as process and protocol of the needful to ensure that the product is maintained at highest peak value. However, quality has been a watch factor that has resulted in industrial productivity birthed by technological innovation. [1] submitted that defining quality from different perspectives depends on the individual philosophical point of view. Whichever perspective adopted among several perspectives available, the authentic definition is the one that was premised around definition of American Society of Quality. American Society of Quality defines quality as an embodiment of totality of manufacturing essence which is positioned to satisfy an implied need or consumers' product need and expectation [1]. Also, [2] viewed quality as an identity of production essence while [3] described quality as collection of different hall-mark of production optimizations, expressed in implementable units. Therefore, it worth a while controlling the process that lead to formulation of quality, then controlling cost at different stage of production would be very easy. The important nature of quality control in industrial manufacturing therefore necessitates the establishment of control system during industrial production process.

ii. Examine the Drivers of Effective Quality Control System Monitoring in

iii. Study Issues and Challenges Involved In Quality Control Systems in

*Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence…*

iv. Profile Critical Factors Influencing Adaptation of Effective Intelligent

In this section review of concept was carried out, and constructs were gleaned from the objectives and the aim and the title of this study. Therefore the review covers the following area: quality control, areas of disruption in quality monitoring and intelligent manufacturing. It includes the following: intelligent manufacturing system, quality control in manufacturing industry, industry 4.0 application disruption in quality assurance monitoring and challenges in quality control system.

The world of manufacturing environment has changed drastically in recent times, on account of industrialization. Also paradigm in production process, design and implementation has shifted in the direction of application of new generation applications, the applications could be found in design, monitoring and marketing industries. The new application has capability to accommodate high volume product processing, complex system and flexible schedule and sequence. The new system is referred to as intelligent system. The word intelligence comes from the new packages that comes with electronic tools that are now in popular use in industrial manufacturing [9]. The authors described intelligent system as electronic and automation replacement of traditional mechanical functions with new applications that uses sensors and sensitive Nano-tubes applications. In another clime, it is referred to as automatic system which found integration in design and monitoring system as

Intelligent system is highly used in monitoring process during industrial manufacturing of products. Intelligent production systems are operated as a calibrated design and monitoring system, they are used in sequential monitoring of production system. They are used to monitor highly complex manufacturing system in order to achieve flexible manufacturing for instance, [10–12] submitted that intelligent system has enabled the use of sensor, optimization parameters, laser beam application and laser beam machine process. This according to [10] described the introduction of intelligent manufacturing system as a step ahead of traditional manufacturing system. The claim lies in the fact that intelligent manufacturing has capability of self-analyzing, self-learning, complexity apprehensions and large data storage. The self -analyzing attribute of systems of intelligent component is rooted in attribute of intelligent application that consist of the use of sensors. The sensors are mounted on tools and machine for quality control attribute in areas such as sequencing, intelligent scheduling, intelligent control and maintenance.

Moreover, in intelligent manufacturing, scheduling and sequencing are "sinqua-non" there is interrelationship between the two concepts. The concepts tend to reoccurs throughout the production process because of its high utility. Also, [13] posited that intelligent algorithm was designed to assist in parametric calibration of some intelligent applications used in manufacturing industries. Algorithms are used

Intelligent Manufacturing

*DOI: http://dx.doi.org/10.5772/intechopen.93979*

Intelligent Manufacturing

Manufacturing Process.

**2.1 Intelligent manufacturing system**

**2. Literature review**

pointed out in [9, 10].

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Quality control system according to [3, 4] ensures emergence of quality product as output of manufacturing process. Quality control system enables the engagement of different techniques and process to ensure quality production output. Some of the techniques according to [4–6] has yielded tremendous results in the past and still remain relevant in the scope of industrial production and manufacturing till date.

However, some of the techniques and tools are gradually becoming obsolete and yielding reduced performance in term of output, therefore there is a need for gradual replacement of old methods with automation techniques, in order to sustain the tempo of productivity. This fact necessitate research in the area of quality assurance in industrial manufacturing. Adventure for development of new quality assurance system and methods of production that is automation based lead to evolution of Industry 4.0, which has since then changed the industrial manufacturing game [6]. Introduction of industry 4.0 with artificial intelligence into the manufacturing system has brought about replacement of old mechanical based method with new and smarter machine technique with automated system that uses sensors, this according to expert has changed procedures often used in quality checks in manufacturing sector. However, artificial intelligence has brought up application of robotics in industrial application and also the use of applications that has been empowered with sensors for automation capability. Smarter machine according to [5, 7] has led to enhanced productivity, improved quality standard and products.

Finally, in [5, 8] it was alluded that innovation of smarter machines, sensor enable machine has been a major addition from industry 4.0 technological disruption, that brought about intelligent manufacturing, it is on this premise that this study investigated system and process of adapting disruption technology in quality control monitoring to be able to achieve results oriented intelligent manufacturing.

#### **1.1 Aim and objectives**

#### **1.2 Aim**

The aim of the study is to carry out a study on application of disruptive application in managing quality system in intelligent manufacturing with a view to improving manufacturing process in organizations.

#### **1.3 Objectives**

There is a need to articulate objectives of the study, the objectives were synthesis from the gaps and emerging thoughts from literatures consulted. Therefore the following objectives are used in this study. They are to:

i. Investigate the state of disruption in quality monitoring in industrial manufacturing

*Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence… DOI: http://dx.doi.org/10.5772/intechopen.93979*


## **2. Literature review**

In this section review of concept was carried out, and constructs were gleaned from the objectives and the aim and the title of this study. Therefore the review covers the following area: quality control, areas of disruption in quality monitoring and intelligent manufacturing. It includes the following: intelligent manufacturing system, quality control in manufacturing industry, industry 4.0 application disruption in quality assurance monitoring and challenges in quality control system.

#### **2.1 Intelligent manufacturing system**

The world of manufacturing environment has changed drastically in recent times, on account of industrialization. Also paradigm in production process, design and implementation has shifted in the direction of application of new generation applications, the applications could be found in design, monitoring and marketing industries. The new application has capability to accommodate high volume product processing, complex system and flexible schedule and sequence. The new system is referred to as intelligent system. The word intelligence comes from the new packages that comes with electronic tools that are now in popular use in industrial manufacturing [9]. The authors described intelligent system as electronic and automation replacement of traditional mechanical functions with new applications that uses sensors and sensitive Nano-tubes applications. In another clime, it is referred to as automatic system which found integration in design and monitoring system as pointed out in [9, 10].

Intelligent system is highly used in monitoring process during industrial manufacturing of products. Intelligent production systems are operated as a calibrated design and monitoring system, they are used in sequential monitoring of production system. They are used to monitor highly complex manufacturing system in order to achieve flexible manufacturing for instance, [10–12] submitted that intelligent system has enabled the use of sensor, optimization parameters, laser beam application and laser beam machine process. This according to [10] described the introduction of intelligent manufacturing system as a step ahead of traditional manufacturing system. The claim lies in the fact that intelligent manufacturing has capability of self-analyzing, self-learning, complexity apprehensions and large data storage. The self -analyzing attribute of systems of intelligent component is rooted in attribute of intelligent application that consist of the use of sensors. The sensors are mounted on tools and machine for quality control attribute in areas such as sequencing, intelligent scheduling, intelligent control and maintenance.

Moreover, in intelligent manufacturing, scheduling and sequencing are "sinqua-non" there is interrelationship between the two concepts. The concepts tend to reoccurs throughout the production process because of its high utility. Also, [13] posited that intelligent algorithm was designed to assist in parametric calibration of some intelligent applications used in manufacturing industries. Algorithms are used in Asia and European industrial manufacturing sectors in permutation control of scheduling and sequencing operation. Scheduling operations involved scheduling of machine operations, allocation of resources of money, man, human and machine among others. [12, 14] in scheduling operations, parameters setting is of utmost importance. Some of the parameters was discovered by Johnson in 1965, scheduling was classified by Johnson into two categories; the flow shop and job shop. In concurrent intelligent scheduling, the flow shop utilizes Toyota production system in a way that the system could accommodate large volume of work per time, this view was supported in [14–17].

reliability is also another measure introduced in ensuring quality in product development [22] presented quality control methods that could be used to enhanced productivity and safety [23]. Worked on systematic ways of presenting reliability analysis of control system, that, it has tendency of improving product reliability, strategies and implementation. System and reliability analysis is for the purpose of quality control during product design and manufacturing and control stage. The system was described in [22] as consist of mathematical model that can be used to describe relationship between product quality and control method. Product reliability process design include process conception, identification of product

*Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence…*

**2.3 Industry 4.0 application disruption in quality assurance monitoring**

automation at various aspect of manufacturing. Generation of traditional

Industrial application in product manufacturing has introduced dimension of

manufacturing has metamorphosized into conventional system, thus, the new generation of industrial application covered different systems of conventional technology. In [24], systems that could enable product supply system to be optimized using key technologies such as cyber system, IoT (Internet of things), data analytics, big data, and expanded database. The key production points could be interlinked and interconnected or networked for effectiveness. Industry 4.0 enables digital interconnectivity among machine and work stations of production system. Similarly, industry 4.0 facilitates the interoperability of man and machine interconnected with digital guides [25]. However, industry 4.0 has different adaptability in different continent both in literary presentations and industrial application. In Japan, industry 4.0 is embellished as "New strategy", China captured it as Made-in-Chine 2025 as contained in {48} while United states according to [24] referred to industry

Industry 4.0 involved is centered on industrial reformation or reindustrialization and information applications contained in [26], this fact was corroborated by [27], which makes availability of quality supervisors and production managers. In nutshell, the component of industry 4.0 application in the portfolio of industrial manufacturing and production according as an inclusive component as viewed by [25, 28–30] and it consist of the following aspects in industrial production: IoT applications, learning factories, internet services, cloud computing and storage, cybernetics, cognitive computing, Artificial intelligence, robotics, data analytics, mechatronics, big data application, and sensor management among others.

Right from the ancient days of product manufacturing, industrial application has

experienced a lot of changes ranging from design parameters configuration of product design implementation. Companies and design expert has labor extensively to come up with perfect system, but there has always been one challenge or the other. Quality control system in intelligent manufacturing gas come with challenges. [31] Deloitte (2014) opined that, there are challenges associated with indus-

Challenge of making reliable forecast is one of the major challenges often encounter in quality control management, however, [32] opined that the use of cyber technology equipment, physical system, artificial intelligence, big data would increase efficiency of running production system. Similarly, ineffective flow of materials and adequate planning has always been the bane of effective production

**2.4 Challenges in quality control system research (quality control**

manufacturing process and robust design [22, 23].

*DOI: http://dx.doi.org/10.5772/intechopen.93979*

4.0 as "reindustrialization".

**implementation in**

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try 4.0 digitalization and digital transformation.

The choice of scheduling technique often depends on complexity, desired output and volume of system at hand. There are two conditions under which scheduling could be applied, the flow shop and job shop. Flow Shop in manufacturing and production process refers to high volume system that uses highly standardized equipment to ensure continuous flow of standardized products e.g. refineries, cement company, drinks production. Similarly, Job Shop is a low volume system, which periodically shift from one job to another. The production is often according to consumers'specification and orders are in small units [16, 17]. Moreover, sequencing is about methodical approach to processing loading jobs at work station. It describes the order in which jobs are processed or should be processed at work centers. In traditional scheduling operation the following rules subsists; the widely acceptable rules for scheduling operation in intelligent manufacturing according to [16–18] includes the following: First come First Serve (FCFS): Processing job in the order of arrivals at work center. Shortest Processing Time (SPT): Job are processed based base on length of processing time and Earliest Due Date (EDD): This rule sequences jobs according to their due date. Shortest due date are processed.
