Human reliability analysis and optimization of manufacturing systems through Bayesian networks and human factors experiments: A case study in a flexible intermediate bulk container manufacturing plant

Abstract Human reliability analysis (HRA) and optimization in manufacturing systems are effective to reduce system failure. The purpose of this study is to examine the HRA and optimization through a Bayesian network (BN) model and human factors experiments (HFEs). This study was applied to a flexible intermediate bulk container manufacturing plant. The human physiological and psychological factors consisting of personal abilities of flexibility, coordination, memory, and attention were regarded as the only performance shaping factors in this study. With the BN model, the relationship between human factors and human errors was described qualitatively and the impact of the human factor on system failures was judged quantitatively. Then the workers’ abilities training with HFEs based on the fault diagnosis results was carried out. The total numbers of errors have been decreased by 69.06% and the system failure rate has been reduced significantly after training.