Agent based simulation of workers' behaviours around hazard areas in manufacturing sites

Hanane El-Raoui, John Quigley, Andrew Sherlock, Ayse Aslan, Jonathan Corney, Jack Hanson, Gokula Vasantha

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

Rewards for risk taking behaviour by workers (if accidents do not occur) can be realised in the form of increased productivity or worker idle time. However, frequent unsafe behaviours of workers inevitably results in accidents and an associated loss in productivity. Workers' behaviour towards safety is influenced by management, who can encourage or discourage risk taking behaviour. In this paper, we explore the relationship between the perceived reward by individual workers who expose themselves to hazards and a management response in the form of inspections to monitor and address inappropriate behaviours. We conduct this study by developing an Agent Based Simulation Model, where workers are required to learn paths within a factory exposed to hazardous areas, with inspectors randomly moving around the factory to correct inappropriate behaviour if noticed. We assume workers are maximising their anticipated reward as they learn routes through the factory. This agent based model is used to explore the impact of inspection frequency and reward perception (i.e. parameters which can be influenced by management) on the number of workplace accident. The results demonstrated that the proposed model is a valuable tool to assist the management in predicting the potential safety improvement from safety management practices focusing on safety inspections, and changing workers perceptions.
Original languageEnglish
Title of host publicationProceedings of the Simulation Workshop 2023
Publication statusPublished - 5 Apr 2023

Keywords

  • manufacturing
  • workers behaviour
  • safety

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