# Intelligent Framework Design for Quality Control in Industry 4.0
## 1 Introduction  
Quality control is an essential process to ensure that a product meets the expected standard and customer expectations, which enhances loyalty and satisfaction. Quality control helps detect faulty and defective products and thus avoid costly recalls and material wastage. QC helps in complying with regulation and safety protocols and thus avoids legal issues and protects the reputations of businesses. By the early detection of anomalies in a product, quality control can minimize product failure and safeguard the finances and reputations of businesses. Quality control has evolved through the ages by technological and industrial advancements. Initially, QC was managed by experts and individual craftsmen. These craftsmen were reputed for their workmanship [1]. Then came the first industrial revolution, which saw the rise in industries and mass production. The first industrial revolution shifted the focus from experts and individual craftsmen to production line efficiency [2]. The second industrial revolution evolved in the early 20 th century and saw the introduction of standards and management methods. Statistical methods, including control charts, were developed to monitor and manage production quality [3]. Total Quality Management (TQM) emerged in the third industrial revolution, emphasizing continuous improvement, customer focus, and employee involvement. The implementation of ISO standards and the Six Sigma brought superior QC practices as it made use of international standards and statistic tools for decreasing defects [4]. The integration of technologies likeAI, the Internet of Things, and cloud computing has transformed QC with smart factories and sophisticated monitoring systems. AI and machine learning continue to enhance QC, enabling more adaptive and autonomous systems. This era is termed Industry 4.0 or the fourth industrial revolution. Overall, QC has evolved from manual inspections to complex, data-driven systems, reflecting technological advancements and changing industry and consumer demands. Two facets of quality control are the subject of this study, pre-production quality control and post-production quality control. The goal of pre-production quality control is to ensure that the production machines are in good working order since this directly affects the quality of the products that the machines will produce. The target is the gear of an induction motor used in manufacturing. Post-production quality control examines the condition of products that have previously been manufactured in Section 2. To assess quality control after manufacture, we use the hex nut as a test product. In many industrial applications, machinery performance--especially that of gears--must be optimal. On the other hand, gear problems can result in expensive downtime, lower production, and even safety risks [5]. Reactive methods are frequently used in traditional maintenance procedures, which can lead to unanticipated failures and consequent operational disruptions. Therefore, to avoid unplanned shutdown and catastrophic failure, an early prediction of faults and proactive maintenance of the gear system is in high demand. The use of both vibration data as the input feature (to monitor health) and the labeled output results corresponding to time domain features is a very interesting method that can be broadly used for gear fault prediction. Vibration signals contain significant information on gear conditions, such as wear, cracks, and misalignment [6]. Vibration data analysis provides an effective way to monitor trends that indicate impending failure and schedule timely repair procedures for risk mitigation as well as extending the life of the industrial machines. Although multiple benefits are included, this method is accompanied by some challenges during the implementation of gear fault prediction and health monitoring systems based on vibration data. Secondly, in the modern manufacturing industries, it is essential to prioritize product quality to satisfy customers, stay competitive, and adhere to regulations.