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Designing Cyclic Job Rotations to Reduce the Exposure to Ergonomics Risk Factors.

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  • 1Instituto de Investigación e Innovación en Bioingeniería (I3B), Universitat Politècnica de València, Camino de Vera s/n, 46022 València, Spain.

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This study introduces an evolutionary algorithm to create job rotation schedules, minimizing injury risks and worker fatigue. The approach optimizes ergonomics, reducing musculoskeletal disorder potential in complex work environments.

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evolutionary algorithmsjob rotationmusculoskeletal disorders

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Area of Science:

  • Occupational Health
  • Ergonomics
  • Computer Science

Background:

  • Job rotation is a common strategy to prevent work-related musculoskeletal disorders.
  • Developing effective job rotation schedules is complex due to multifactorial health risks and workplace constraints.

Purpose of the Study:

  • To present an evolutionary algorithm for generating optimized job rotation schedules.
  • To reduce the potential for work-related musculoskeletal injuries and minimize worker fatigue.

Main Methods:

  • An evolutionary algorithm was developed to generate cyclic job rotation schedules.
  • The algorithm clusters tasks, selects workers for rotation groups, and determines rotation sequences.
  • Optimization focused on multiple ergonomics criteria to mitigate injury risks.

Main Results:

  • The algorithm generates schedules that reduce prolonged exposure to musculoskeletal injury risks.
  • It simplifies worker assignment to different tasks within rotation cycles.
  • The approach effectively balances ergonomic improvements with workplace productivity constraints.

Conclusions:

  • The evolutionary algorithm is an effective tool for designing job rotation schedules.
  • It helps prevent work-related musculoskeletal disorders by optimizing task rotation and worker assignment.
  • The procedure simplifies schedule management and facilitates job monitoring.