חיפוש מתקדם

Yaar Harari, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel (e-mail: yaar@post.bgu.ac.il).

Raziel Riemer, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel (e-mail: rriemer@bgu.ac.il).

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.

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הספר "אוצר וולקני"
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תנאי שימוש
Simulation-Based Optimization Methodology for a Manual Material Handling Task Design That Maximizes Productivity While Considering Ergonomic Constraints

Yaar Harari, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel (e-mail: yaar@post.bgu.ac.il).

Raziel Riemer, Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel (e-mail: rriemer@bgu.ac.il).

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.

Scientific Publication
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