Workforce reconfiguration strategies in manufacturing systems: a state of the art

ABSTRACT

This paper provides a literature review and an analysis of the studies related to workforce reconfiguration strategies as a part of workforce planning for various production environments. The survey demonstrates that these strategies play a crucial role in the resilience and flexibility of manufacturing systems since they help industrial companies to quickly adapt to frequent changes in demand both in terms of volume and product mix. Five strategies are considered: the use of utility, temporary, walking, cross-trained workers, and bucket brigades. They are analysed in the context of mixed and multi-model manual assembly lines, dedicated, cellular, flexible, and reconfigurable manufacturing systems. The review shows that most of the researches on these reconfiguration strategies focus on multi- or mixed-model assembly lines. At the same time, few studies consider workers team reconfiguration in flexible and reconfigurable manufacturing systems. Finally, this paper reveals several promising research directions in workforce reconfiguration planning, namely, the use of both machine and workforce reconfigurations, consideration of the ergonomic aspects, the combination of multiple workforce reconfiguration strategies, the study of workforce reconfiguration in human-robot collaborative systems, and the use of new technologies in human-machine industrial environments.

KEYWORDS:

• Workforce planning
• workforce assignment
• flexibility
• reconfigurability
• reconfiguration strategies
• reconfigurable manufacturing systems
• assembly lines
• operations management
• state of the art
• survey
• review

Acknowledgements

The authors of this paper would like to thank the Region Pays de la Loire, France (www.paysdelaloire.fr) for financial support of this study.

Disclosure statement

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

Additional information

Notes on contributors

S. Ehsan Hashemi-Petroodi

Seyyed Ehsan Hashemi-Petroodi is a Ph.D. student in Automation, Production, and Computer Science Department at the IMT Atlantique, France. He received two master diplomas in Industrial Engineering from a joint programme between University of Tehran (UT), Tehran, Iran and École Nationale Supérieure d’Arts et Métiers (ENSAM), Paris, France in 2018. He worked on Simulation-Based Optimisation Approaches for Reconfigurable Manufacturing Systems. Currently, his Ph.D. is supervised by Prof. Alexandre Dolgui, Dr. Simon Thevenin, and Dr. Sergey Kovalev. He is working on Combinatorial Optimisation Approaches for Reconfigurable Assembly Line Design and Balancing. His research interests focus on Manufacturing Line Design, Workforce Planning, Mathematical Programming, Exact Optimisation Methods, and (Meta-)Heuristics.

Alexandre Dolgui

Alexandre Dolgui is an IISE Fellow, Distinguished Professor, and the Head of Automation, Production and Computer Sciences Department at the IMT Atlantique, France. His research focuses on manufacturing line design, production planning and supply chain optimisation. His main results are based on the exact mathematical programming methods and their intelligent coupling with heuristics and metaheuristics algorithms. He is the co-author of 5 books, the co-editor of 20 books or conference proceedings, the author of 252 refereed journal papers, as well as over 400 papers in conference proceedings. He is the Editor-in-Chief of the International Journal of Production Research (IJPR).

Sergey Kovalev

Sergey Kovalev is an Associate Professor in INSEEC School of Business & Economics. He obtained a Ph.D. degree in industrial engineering in Ecoles Nationale Supérieure des Mines de Saint-Etienne in 2012. In 2013–2014 he worked on the development of optimisation support module of the FP7 European Project amePLM – Advanced Platform for Manufacturing Engineering and Product Lifecycle Management. He continues the research on workforce assignment problems initiated during this project. He is a specialist in combinatorial optimisation, which has practical applications in practically every area of human activity. Most of his research is dedicated to assembly line balancing and scheduling problems applicable in production planning and project management.

Mikhail Y. Kovalyov

Mikhail Y. Kovalyov is a Deputy General Director for Research of the United Institute of Informatics Problems (Minsk, Belarus) and corresponding member of the National Academy of Sciences of Belarus. He has contributed to the theory of fully polynomial time approximation schemes, scheduling, production research, computational complexity, algorithm design, logistics, bio-informatics. He has published in top Operational Research, Computer Science and Industrial Research journals. He is involved in the editorial work of the journals Computers and Operations Research, European Journal of Operational Research, INFORMS Journal on Computing, Omega and Journal of Scheduling.

Simon Thevenin

Simon Thevenin is an assistant professor in the Automation, Production, and Computer Sciences Department at the IMT Atlantique, France. He received a Ph.D. from the University of Geneva in 2015 for his work on metaheuristics to solve scheduling problems in production systems. His current research interests focus on optimisation methods for production management, including production scheduling, production planning, and manufacturing line design.