**2.2 Quality control in manufacturing industry**

In manufacturing sectors there have been gaps in the users request for product and the quantity of product manufactured to meet the requests, this trend, tend to permit packaging low quality products into markets. However, high level of quality is demanded as part of users demand expectation. In contemporary times, users expect faultless product, which has put more pressure on the manufacturer and their production outfits. Therefore, there should be shift from traditional ways of enforcing quality so as to enhance manufacturing productivity. Manufacturers' bid to improve quality has led cutting edge researches in quality control process, this therefore lead to new realm where quality control methods and processes are digitalized and this concept is termed quality 4.0. Quality 4.0 borders about the use of enhanced system to collect information about the design, behavior, use and performance of products in market. The quality 4.0 involve the use of benefits of Artificial intelligence (AI). Artificial intelligence works according to [19] through identifying faults in product with AI algorithm, the AI algorithm having been calibrated in fault identification would notify quality team of emerging faulty product. Similarly, quality control charts are often used alongside with AI in quality monitoring and also through pictorial illustration of quality trend in production batch, for instance in [20] simple statistical analysis method was used in interpreting quality results. It was noted in [21], that Japan adopted statistical method and tools in quality management. In Japan, certain quality control system has been in use in the manufacturing sector, for instance [20] submitted that the following system has been consistently engaged in intelligent manufacturing quality control in Japanese production process; Ishikawa, flow chart, figure and diagrams, pareto analysis, checklist and correlation among others. [21] identified six sigma template as being a useful tools as well in quality control monitoring process. Similarly, product

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

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 manufacturing process and robust design [22, 23].

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

Industrial application in product manufacturing has introduced dimension of automation at various aspect of manufacturing. Generation of traditional 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 4.0 as "reindustrialization".

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.
