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Raziel Riemer

Senior Academic

Simulation-Based Optimization Methodology for a Manual Material Handling Task Design That Maximizes Productivity while Considering Ergonomic Constraints

Design of workplaces that include human-machine systems and manual material handling should consider both the productivity of workers and the risk of injury. In this study, a simulation-based optimization methodology for a manual material handling task design was developed. A new formulation of the optimization problem is presented, whose objective is to maximize worker productivity and at the same time not to exceed ergonomic thresholds (which represent injury-risk measures). The workplace and work process were simulated using digital human modeling software (Jack), and the best design was found using a genetic algorithm. The results show that the new formulation of the optimization problem improved the predicted productivity by 105%, compared to the formulation used in previous studies that used a multi-objective function. Meanwhile, the risk of injury did not exceed ergonomic thresholds.

Publication language English
Pages 440-448
Journal IEEE Transactions on Human-Machine Systems
Volume 49
Issue number 5
Publication status Published - 01.10.2019
Article Number 8665911

Keywords

Computational human modeling
ergonomics
human performance
manual material handling task design
optimization

ASJC Scopus subject areas

Human Factors and Ergonomics
Control and Systems Engineering
Signal Processing
Human-Computer Interaction
Computer Science Applications
Computer Networks and Communications
Artificial Intelligence
Access to Document
10.1109/THMS.2019.2900294
Other files and links
Link to publication in Scopus