Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance

Abstract

This research applies agent-based modelling (ABM) to study volume flexibility in a dual resource constrained (DRC) assembly flow shop environment. The simulation experiment evaluated system and human effects of varying DRC system staffing levels according to design (i.e., workforce, distance and buffer capacity), sensitivity (i.e. coefficient of variation) and operating (i.e. when rule and where rule) factors. Results showed that the rule by which workers are assigned to workstations affects WIP and flow time performances more than production rates. Furthermore per-worker productivity was found to increase, compared to the fully staffed system, particularly where the downstream movement rule was applied. Using the downstream rule when changing stations after completing current tasks reduced flow time (−15%) and WIP (−10%). If another where rule is chosen then it may be preferable for workers to move only after completing all jobs in the station (decentralised rule). For utilisation rates and mean hourly switching of work (human effects), the model shows complex relationships depending on almost all evaluated factors. The novel ABM approach used here enabled the evaluation of emergent system behaviours and showed potential to help firms understand both human and performance effects of operational choices in efforts to achieve volume flexibility.