Human factors under uncertainty: A manufacturing systems design using simulation-optimisation approach

Authored by Jelena Petronijevic, Alain Etienne, Jean-Yves Dantan

Date Published: 2019

DOI: 10.1016/j.cie.2018.11.001

Sponsors: No sponsors listed

Platforms: AnyLogic

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Modern manufacturing systems are characterized by waste elimination, cycle time control, and high work specifications. Workers, although being an integral part of manufacturing, are usually neglected or severely simplified in operational research of these systems. Through the years, the need for control over the job in manual manufacturing has been identified as crucial for both system performances and operators' health. The aim of this research is to integrate time margins, as the mean of control, and human factors under uncertainty into scheduling problem of a multi-product manufacturing system while maintaining performance and workers' well-being. The proposed method is polynomial and simulation-based, developed in two stages using agent based methodology. The first stage provides a global schedule with makespan as the objective function and with time margin allocation strategy under uncertainty. The second stage enables rescheduling depending on the human error probability and fatigue level. Experiments and comparisons with the similar literature problem have indicated decrease of human error probability and fatigue. Extended experiments for flow shop system justify the use of this unique approach. The developed tool enables system designers to enhance performance by observing human effects through its factors and different time margins allocation strategies.

Tags

Uncertainty models environment Human factors scheduling Integration Framework Algorithm Agent-based modelling Musculoskeletal Machines Time margins Flow system Flow-shop Job demands Fatigue