Production risk analysis and prioritization in manufacturing industry: A hybrid approach using Monte Carlo simulation and DEMATEL analysis

Abstract

Risk identification and prioritization in production sector is critical if an enterprise wishes to compete successfully. To achieve this, Delphi technique was utilized to finalize 36 identified risks in a ‘metal plate production’ stage prior to risk analysis through risk probability and its impact. Risk prioritization is performed by Monte Carlo Simulation (MCS) and Decision Making and Trial Evaluation Laboratory (DEMATEL) analysis. The novelty of this study is to develop an effective hybrid approach by utilizing strengths of MCS (with iterations in thousands on the simulation) as well as DEMATEL analysis (to assess the causal relationship among risk factors). A more accurate risk identification by developing a consolidated list of risks in one of the important production stages followed by an efficient prioritization of interacting (process and product related) risks will help the shop floor operator making better decisions to enhance the quality by minimizing production time and cost.