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Human reliability modeling in occupational environments toward a safe and productive operator 4.0

  • Setareh Kazemi Kheiri
  • , Zahra Vahedi
  • , Hongyue Sun
  • , Fadel M. Megahed
  • , Lora A. Cavuoto
  • SUNY Buffalo
  • Miami University

Research output: Contribution to journalReview articlepeer-review

20 Scopus citations

Abstract

Many occupational environments require labor intensive activities, which could result in fatigue and injuries and cause decreased work performance. Recently, the breakthroughs of Industry 4.0 have allowed for tracking worker conditions. Based on these, various analytical models have been performed with the aim of guiding work design in occupational environments, which contributes to ultimately achieving a safe and productive Operator 4.0. However, there is a lack of systematic analysis and implementation guidelines. In this paper, we review the literature on upper-limb fatigue modeling in occupational settings, since it is reported shoulder injuries are a pressing issue. From the reviewed papers, our main observations are that the majority of studies focus on identifying human fatigue/reliability indices, and the corresponding factors contributing to these indices, through statistical and biomechanical models. However, existing models lack the consideration of several important aspects of upper-limb fatigue analysis, such as the full use of wearable sensor data in a real-time manner, consideration of the heterogeneity of workers and measurement devices, and the difference between simulated and actual work environment. Moreover, the issue of fatigue development for the workers' upper extremities, which could significantly have an impact on workers' performance, has not yet been studied from a system reliability point of view to the best of the authors’ knowledge. Reliability engineering models that are widely used to model machines can play an important role in modeling humans in occupational settings. We discuss the limitations of the reviewed articles and provide insights for future research.

Original languageEnglish
Article number103479
JournalInternational Journal of Industrial Ergonomics
Volume97
DOIs
StatePublished - Sep 2023

Keywords

  • Human reliability analysis
  • Operator 4.0
  • Upper-limb fatigue
  • Wearable sensors

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