Abstract
Real-world manufacturing supply chain systems are characterised by imprecise and dynamic factors. As a result, decision-making takes place in a complex, dynamic and fuzzy environment in which managerial goals and the impacts of possible actions are not precisely known. In a demand driven manufacturing supply chain system, the presence of a fuzzy demand is a serious cause for concern. The present study integrates fuzzy theory and system dynamics simulation to address the fuzzy and dynamic nature of demand-supply factors, from a systems perspective. A set of performance indices were defined to evaluate the system performance. Based on typical demand scenarios, comparative simulation experiments were conducted using the base scenario as a benchmark. The simulation results show the utility of the fuzzy system dynamics approach: (a) the approach represents the real-world picture of a supply chain with fuzzy demand, (b) the supply chain system performs better under dynamic fuzzy policies, and (c) computational “what-if analysis” showed that dynamic fuzzy-based policies are more robust than conventional crisp rules, even in turbulent demand situations. Further managerial insights and practical evaluations are provided in this study.