Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Abstract

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.

Millimeter-Wave Smart Antenna Solutions for URLLC in Industry 4.0 and Beyond

“…Out of three vertices of a 5G triangle, i.e., enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and URLLC, the factory automation scenario fits best under URLLC category to ensure millisecond-level delay in smart communication [ 35 , 36 ]. Moreover, with the emergence of ever more sophisticated applications (such as holographic telepresence, virtual reality, augmented reality, visual capabilities for smart robots and automatic guided vehicles, mass customization and personalization of products), the sixth generation of wireless technology (6G) has also emerged as an enabling technology to enhance the efficiency and scalability of the communication system [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 ]. As a result, traditional sub-6 GHz wireless communication cannot meet URLLC requirements of Industry 4.0 and beyond because the unlicensed spectral resources in the low-frequency bands (e.g., 2.4 GHz and 5 GHz) are limited.…”

“…In the context of Industry 4.0 and beyond, the requirements for quality of service (QoS) and quality of data (QoD) are much more stringent [ 28 , 41 ]. QoS mainly includes high reliability, real-time operation, agility, seamless connectivity, security, and privacy.…”

Energy Key Performance Indicators for Mobile Machinery

“…is the first gap of industrial needs [12][13][14]. There is no doubt that KPIs have enormous potential as a comparative method of machine performance and, consequently, a tool in monitoring continuous improvement [15].…”

Fast Fault Diagnosis in Industrial Embedded Systems Based on Compressed Sensing and Deep Kernel Extreme Learning Machines

“…Due to a large number of checkpoints, high sampling rate and long detection time, the health monitoring system has acquired massive status data. On the one hand, it has prompted the fault diagnosis of complex industrial systems to move into the “data-driven” era [ 2 ], on the other hand, it has also brought great difficulty to fast fault diagnosis in resource-constrained industrial embedded systems [ 3 ].…”