Abstract
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.
Original language | English |
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Article number | 8665911 |
Pages (from-to) | 440-448 |
Number of pages | 9 |
Journal | IEEE Transactions on Human-Machine Systems |
Volume | 49 |
Issue number | 5 |
DOIs | |
State | Published - 1 Oct 2019 |
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