The Fourth Industrial Revolution, also known as Industry 4.0 (I4.0), has significantly transformed the manufacturing industry by integrating modern smart technologies, such as the Internet of Things (IoT) and Cyber Physical Systems (CPS). This integration has led to the emergence of "Smart Manufacturing," which has enabled the production of dynamic, flexible, and self-organized manufacturing systems. Quality 4.0 (Q4.0) has since stemmed from I4.0 and aims to digitalize quality management practices, aligning them with the emergent capabilities of I4.0 to achieve excellence.
A systematic literature review was conducted to investigate the impact of I4.0 on improving quality management practices and the challenges hindering Q4.0 adoption. The review analyzed 52 articles and found that I4.0 technologies have the potential to enhance quality management approaches through real-time and continuous monitoring systems, defect prediction systems, in-line intelligent quality control, and total inspection solutions. Other benefits include data-driven decision making, increased responsiveness, and improved customer satisfaction, as well as significant cost reductions due to early defect detection and root cause elimination.
However, the review also highlighted some research gaps, such as the lack of use cases and case studies, a comprehensive theoretical definition of Q4.0, and the need for more research on the contributions of I4.0 to quality assurance and quality planning. The review suggested that more research is needed on cost-benefit analysis, maturity models for Q4.0 adoption, change management, and culture creation. Additionally, the review pointed out the need to address the gap in research on Q4.0 in service industries such as healthcare and financial services.
Implementing Q4.0 requires the integration of I4.0 technologies such as CPS, IoT, and data analytics, with traditional quality management methods. The aim of Q4.0 is to improve efficiency, innovation, and performance, while enhancing business models within organizations. Q4.0 is not meant to replace traditional quality methods, but rather to build upon them, going beyond technology and maximizing value via embracing users and processes.
The reviewed studies demonstrate the significant role of Industry 4.0 technologies, particularly Big data and analytics, AI, ML, CPS, IoT, and AR, in improving quality control and process monitoring practices. These technologies enable the collection and analysis of real-time data, early defect detection, and self-adaptation techniques, leading to improved product quality and increased customer satisfaction.
In the context of predictive quality, Wang et al. (2020) proposed a framework for intelligent quality prediction based on machine learning techniques. The framework can analyze and process large amounts of data, identify the root causes of quality problems, and provide predictions for future quality performance. Through these approaches, I4.0 can contribute to predictive quality by utilizing advanced analytics and machine learning techniques to facilitate early detection and prevention of quality issues.
The integration of I4.0 technologies in quality management practices has significant potential to improve operational excellence and performance. However, it requires significant investment and organizational changes. The challenges hindering Q4.0 adoption, such as security concerns, lack of cost-benefit analysis, lack of research and development efforts, lack of processing capacity, lack of connection between the operator and the system, and the need for a quality culture, must also be addressed.
Overall, the concept of Quality 4.0 is still relatively new, and more research is needed to explore its full potential and impact on quality management practices. The reviewed studies demonstrate the potential opportunities and challenges of Q4.0, which is the integration of I4.0 technologies and solutions in quality management. The papers highlighted the benefits of I4.0 technologies in obtaining real-time information, faster handling of advanced tasks, automatic and continuous monitoring and alerting, early failure detection, and data-driven decision making. Q4.0 could provide significant benefits to the quality field, but more research is needed to fully understand its potential contributions.
Authors
Saihi, A., Awad, M., & Ben-Daya, M. (2023). Quality 4.0: leveraging Industry 4.0 technologies to improve quality management practices–a systematic review. International Journal of Quality & Reliability Management, 40(2), 628-650. https://doi.org/10.1108/IJQRM-09-2021-0305