An overview on human-centred technologies, measurements and optimisation in assembly systems

Abstract

This paper offers an in-depth examination of the ergonomics of human-centred assembly systems in Industry 4.0, where manual tasks remain essential. The use of advanced technologies such as motion capture (MOCAP) and virtual reality (VR) is analysed as ways to enhance system efficiency and improve worker well-being. The paper highlights the importance of optimising assembly system performance while considering both economic and human factors. Metrics to assess ergonomic risk and productivity are discussed based on human-centred technologies, and existing operational research models are explored to analyse how human factors could be considered in optimising system performance. Additionally, the paper explores potential future directions and how they could play a role in Industry 4.0.

Keywords:

• Human factors
• motion capture
• ergonomics and productivity
• assembly systems
• optimisation

Notes

Data sharing is not applicable to this article as no new data were created or analysed in this study.

Disclosure statement

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

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Rim Slama

Rim Slama is a lecturer and researcher at CESI LINEACT in Lyon, France. She worked for two years at Artec Group in Luxembourg as a researcher, focussing on 3D data analysis and pattern recognition. She also worked as an associate professor at Henallux Engineering School in Belgium. In 2014, she earned a PhD from the University of Lille in France. She received both her MSc (2011) and Engineering (2010) degrees in Computer Science from the National School of Computer Science (ENSI) in Tunisia. Her research interests include pattern recognition, shape analysis, and computer vision. She has published several refereed journals and conference articles in these areas. Her current research interests include face recognition, human action/gesture detection and recognition, time series modelling, dynamic 3D human body analysis, shape matching, and their applications in medical and industrial contexts.

Ilhem Slama

Ilhem SLAMA is an associate professor in the optimisation Department at the University of Technology of Troyes, France. She received a Ph.D. from IMT Atlantique, France in 2020 for her work on stochastic approaches to solve scheduling problems in production systems. Her current research interests focus on optimisation methods for production management, including production scheduling, production planning, and manufacturing line design under uncertainty.

Houda Tlahig

Houda Tlahig is an associate professor at CESI Group's LINEACT laboratory. She holds an engineering degree and a PhD in Industrial Engineering, respectively from the Ecole National d'Ingénieurs de Tunis (ENIT), Tunisia and the Institut National Polytechnique de Grenoble (INPG), France. Her research focuses on the optimisation of production systems of goods and services, using operations research tools. She worked, for example, on the optimisation of the hospital logistics and urban mobility systems. Her current research relate on the multi-objective optimisation in the context of Industry 5.0, in particular addressing the challenges of the flexible and sustainable job shop scheduling problem in human-centered manufacturing systems.

Pierre Slangen

Pierre Slangen is Professor at IMT Mines Ales (France). He received his State PhD in Physics in 1995 from University of Liege (Belgium). He was mainly working on holography, speckle, interferometry, and digital photographic techniques. Prof. P. Slangen was involved in coupling holographic and speckle techniques with high-speed imaging for time-resolved measurements of shockwaves or hypervelocity impacts. Joining UMR EuroMov “Digital Health in Motion” (IMT Mines Ales, Univ Montpellier), P. Slangen is now coordinator of the Ales Imaging Human Metrology (AIHM) facility, to merge motion capture, EEG and NIRS, EMG, and ECG with health, manufacture or sports live conditions.

Oussama Ben-Ammar

Oussama Ben-Ammar received his Ph.D. in Industrial Engineering in 2014 from Mines Saint-Étienne (France). His area of expertise includes operations research, managing uncertainties in the supply chain, and optimising human factors in the industry. Currently, he holds the position of associate professor at IMT Mines Alès (France). Previously, he worked as an assistant professor at the Centre Microélectronique de Provence Georges Charpak at Mines Saint-Étienne, IMT Atlantique, and the University of Toulouse. He also shared his knowledge as a lecturer at Aix-Marseille University and the École Supérieure du Bois in Nantes. Additionally, he had the opportunity to be a visiting professor at Rennes School of Business and Nottingham University Business School in the United Kingdom. Presently, Oussama Ben-Ammar supervises various research projects, both academic and industrial. He has over 15 publications in international journals, contributed to four book chapters, and presented his work at more than 40 national and international conferences.