Simulating the influence of physical overload on assembly line performance: A case study in an automotive electrical component plant

Appl Ergon. 2019 Sep:79:107-121. doi: 10.1016/j.apergo.2018.08.001. Epub 2018 Aug 16.

Abstract

Although the workstations of a Brazilian automotive electrical harness production line are set close to TAKT time (the production rate required to meet demand), factory performance is compromised regarding: (i) sick leaves due to occupational disease (105 employees last year) and (ii) a production rate at only 42% of capacity. Our objective was to simulate the performance of a production line balanced against physical overload by the addition of an extra workstation. Based on ergonomic work analysis, the study applied System Dynamics at the global observation stage to obtain a systemic interpretation of the factors involved in production line performance. According to the indicators, the alternative configuration reduced physical overload by 36%, which would result in a sick leave rate of 50.8 employees/year (51.6% lower than the current configuration), as well as a production rate at 99% of capacity (a 92.7% increase over the current configuration). We found that reducing physical overload allows the "workforce control" loop to govern the system, producing favorable results. We conclude that setting the work cycle overly close to TAKT time leads to overload, due to the shorter recovery times at the end of each cycle. Thus, it is necessary to seek a balance between efficiency gains through downtime reduction and the physiological recovery of workers.

Keywords: Ergonomics; Human factors; Physical overload; Production line balance; System dynamics.

Publication types

  • Evaluation Study

MeSH terms

  • Adult
  • Automobiles
  • Brazil
  • Computer Simulation
  • Efficiency / physiology
  • Ergonomics
  • Female
  • Humans
  • Male
  • Manufacturing and Industrial Facilities*
  • Occupational Diseases / epidemiology*
  • Occupational Diseases / etiology
  • Sick Leave / statistics & numerical data*
  • Work Performance*
  • Workload / psychology*