The evolution of production scheduling from Industry 3.0 through Industry 4.0

Abstract

Since the Third Industrial Revolution, technology and the global economy have developed rapidly. Driven by market demand and the development of science and technology, the organisational model of the production system has evolved, which has in turn caused changes in the methods of production scheduling. In the context of the newest industrial revolution (Industry 4.0), this review aims to examine the evolution of production scheduling in terms of economics and technology. First, literature on production scheduling is summarised and analysed from the perspectives of centralised/decentralised scheduling, distributed scheduling, and cloud manufacturing scheduling. Second, future challenges and trends in the development of production scheduling are discussed in view of the globalisation of manufacturing and changes in production modes enabled by new technologies. Finally, based on the findings of this review, we make a prediction for the future expansions of the customer-centric value chain as well as changes in product design and production methods brought by product personalisation.

KEYWORDS:

• Production scheduling
• Industry 4.0
• centralised scheduling
• distributed scheduling
• decentralised scheduling
• cloud manufacturing scheduling

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported in part by the National Science Foundation of China [grant number 51775033]; and in part by the Fundamental Research Funds for the Central Universities of China [grant number 2019RC023].

Notes on contributors

Zengqiang Jiang

Zengqiang Jiang was from Yixing, Jiangsu, China. He received his B.S. and Ph.D. degrees in mechanical engineering from Hefei University of Technology, Hefei, Anhui, China, in 2002 and 2006, respectively. From 2006 to 2008, he was an assistant professor at Hefei University of Technology, and became an associate professor in 2008. Since 2011, he has been an associate professor in the Mechanical Engineering Department, Beijing Jiaotong University. Since 2020, he has been a professor in Beijing Jiaotong University. His research interests include intelligent manufacturing systems, life prediction and maintenance optimisation.

Shuai Yuan

Shuai Yuan was born in Huairen, Shanxi, China. He received B.S. and M.S. degree in industrial engineering from Beijing Jiaotong University, Beijing, China, in 2017 and 2020. He is currently pursuing the Ph.D. degree in mechanical engineering at Beijing Jiaotong University, Beijing, China. His research interests include intelligent optimisation and production scheduling.

Jing Ma

Jing Ma was born in Guyuan, Ningxia, China, in 1987. He received the B.S. and Ph.D. degrees in mechanical engineering from Hefei University of Technology, Hefei, China, in 2010 and 2015, respectively. From 2016 to 2018, he was a postdoctoral fellow with Tsinghua University. Since 2018, he has been an assistant professor in the Mechanical Engineering Department, Beijing Jiaotong University. His research interests include intelligent manufacturing systems planning, modeling and optimisation, remaining useful life prediction & maintenance optimisation.

Qiang Wang

Qiang Wang was born in Hefei, Anhui, China, in1987. He received the B.S. and Ph.D. degrees in mechanical engineering from the Hefei University of Technology, Hefei, China, in 2009 and 2016, respectively. Since 2017, he was a postdoctoral fellow with Tsinghua University. Since 2020, he has been an assistant professor in the Mechanical Engineering Department, Beijing Jiaotong University. His research interests include intelligent manufacturing systems, remaining useful life prediction & maintenance optimisation.