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

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

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 languageEnglish
Article number8665911
Pages (from-to)440-448
Number of pages9
JournalIEEE Transactions on Human-Machine Systems
Volume49
Issue number5
DOIs
StatePublished - 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

Fingerprint

Dive into the research topics of 'Simulation-Based Optimization Methodology for a Manual Material Handling Task Design That Maximizes Productivity while Considering Ergonomic Constraints'. Together they form a unique fingerprint.

Cite this