Water Resources & Applied Mathematics Research Lab, Nagpur 440027, Maharashtra, India.
Department of Post Graduate Studies and Research in Mathematics, Jaywanti Haksar Govt. Post-Graduation College, College of Chhindwara University, Betul 460001, Madhya Pradesh, India.
Sensors (Basel). 2021 Dec 29;22(1):224. doi: 10.3390/s22010224.
The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet of Things has enabled smart manufacturing or Industry 4.0. Industry 4.0 refers to the various technologies that are transforming the way we work in manufacturing industries such as Internet of Things, cloud, big data, AI, robotics, blockchain, autonomous vehicles, enterprise software, etc. Additionally, the Industry 4.0 concept refers to new production patterns involving new technologies, manufacturing factors, and workforce organization. It changes the production process and creates a highly efficient production system that reduces production costs and improves product quality. The concept of Industry 4.0 is relatively new; there is high uncertainty, lack of knowledge and limited publication about the performance measurement and quality management with respect to Industry 4.0. Conversely, manufacturing companies are still struggling to understand the variety of Industry 4.0 technologies. Industrial standards are used to measure performance and manage the quality of the product and services. In order to fill this gap, our study focuses on how the manufacturing industries use different industrial standards to measure performance and manage the quality of the product and services. This paper reviews the current methods, industrial standards, key performance indicators (KPIs) used for performance measurement systems in data-driven Industry 4.0, and the case studies to understand how smart manufacturing companies are taking advantage of Industry 4.0. Furthermore, this article discusses the digitalization of quality called Quality 4.0, research challenges and opportunities in data-driven Industry 4.0 are discussed.
大规模生产始于 20 世纪初。在信息和通信技术（ICT）的帮助下，制造业从机械化转变为数字化。现在，ICT 和物联网的进步使智能制造或工业 4.0 成为可能。工业 4.0 是指正在改变我们在制造业工作方式的各种技术，例如物联网、云、大数据、人工智能、机器人技术、区块链、自动驾驶汽车、企业软件等。此外，工业 4.0 概念还指涉及新技术、制造要素和劳动力组织的新生产模式。它改变了生产过程，创建了一个高效的生产系统，降低了生产成本并提高了产品质量。工业 4.0 的概念相对较新；由于缺乏知识和有限的出版物，不确定性很高，涉及工业 4.0 的绩效衡量和质量管理。相反，制造企业仍在努力理解各种工业 4.0 技术。工业标准用于衡量绩效和管理产品和服务的质量。为了填补这一空白，我们的研究重点关注制造业如何使用不同的工业标准来衡量绩效和管理产品和服务的质量。本文回顾了当前用于数据驱动的工业 4.0 中的绩效测量系统的方法、工业标准和关键绩效指标 (KPI)，并进行了案例研究，以了解智能制造公司如何利用工业 4.0 。此外，本文还讨论了质量的数字化，即质量 4.0，讨论了数据驱动的工业 4.0 中的研究挑战和机遇。
