Production and operations management for intelligent manufacturing: a systematic literature review

Abstract

In the context of Industry 4.0, the manufacturing sector is moving from automation towards intelligence. The application of new generation information and communication technologies (ICTs) improves the interconnection and transparency of intelligent manufacturing (IM) systems, which will change how information interacts and work is done, thus changing how work should be managed. These changes require the following characteristics for IM production and operations management (POM): integration, flexibility and networking, autonomous and collaborative decision-making, learning-based operations management, self-optimisation and adaptability, and proactive decision-making. This paper presents the state of the art, current challenges, and future directions of IM-related POM research from the perspectives of these characteristics through a systematic literature review. Descriptive and thematic analyses of 208 research articles published between 2005 and 2020 are provided. The review and discussions focus on five research themes, i.e. value creation mechanisms, resource configuration and capacity planning, production planning, scheduling, and logistics.

KEYWORDS:

• Intelligent manufacturing
• production and operations management
• value creation mechanisms
• resource configuration and capacity planning
• production planning
• scheduling
• logistics

Acknowledgments

The authors are grateful for the comments by the reviewers and editors.

Data availability statement

The data that support the findings of this study are available within the article; supplementary data are available from the corresponding author (Zhibin Jiang) upon reasonable request.

Disclosure statement

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

Additional information

Funding

This work was supported by the National Key Research and Development Program of China [grant number 2018AAA0101700, Task 5] and the National Natural Science Foundation of China [grant number 71931007 and 71871142].

Notes on contributors

Liping Zhou

Liping Zhou received his Ph.D. degree in Industrial Engineering from Shanghai Jiao Tong University (SJTU), Shanghai, China, in 2019. He is currently an Assistant Professor with the Sino-US Global Logistics Institute, SJTU. His research interests include production and service operations management.

Zhibin Jiang

Zhibin Jiang received his Ph.D. degree in Engineering Management from the City University of Hong Kong in 1999. He is currently a Distinguished Professor with the Antai College of Economics and Management, SJTU, Shanghai, China. He is also the Dean of the Sino-US Global Logistics Institute of SJTU. He is a fellow of IISE and an associate editor of the International Journal of Production Research. His research interests include operations management in manufacturing and healthcare systems.

Na Geng

Na Geng received her Ph.D. degree in Industrial Engineering from the Ecole Nationale Superieure des Mines de Saint-Etienne, Saint-Étienne, France, and Shanghai Jiao Tong University (SJTU), Shanghai, China, in 2010. She is currently a Professor with the Sino-US Global Logistics Institute, SJTU. Her research interests include production and service operations management. Dr. Geng has been an Associate Editor of the Flexible Service and Manufacturing journal since 2017, an Associate Editor of the IEEE Transactions on Automation and Science Engineering since 2021, and an Associate Editor of the Health Care Management Science since 2021.

Yimeng Niu

Yimeng Niu is a Ph.D. candidate in Management Science and Engineering from Antai College of Economics and Management, SJTU, Shanghai, China. Her main research interests include servitization of manufacturing firms, and supply chain and operations management.

Feng Cui

Feng Cui is a Ph.D. candidate in Management Science and Engineering from Antai College of Economics and Management, SJTU, Shanghai, China. His main research interests include manufacturing operations management.

Kefei Liu

Kefei Liu is a Ph.D. candidate in Management Science and Engineering from Antai College of Economics and Management, SJTU, Shanghai, China. Her main research interests include manufacturing operations management.

Nanshan Qi

Nanshan Qi is a Ph.D. candidate in Management Science and Engineering from Antai College of Economics and Management, SJTU, Shanghai, China. Her main research interests include manufacturing operations management.