Adaptive production control of two-product closed-loop supply chain dynamics under disruptions

Abstract

ABSTRACTThis paper addresses the dynamics of a two-product closed-loop supply chain with realistic assumptions on production capacity constraints. The closed-loop supply chain is also subject to unpredictable disruptions, which lead to the non-stationarity of customer demand. The factory employs a production control policy to decide the product type to be processed. We propose a novel production control policy, named the Adaptive Hedging Corridor Policy, which makes decisions on production capacity based on the demand evolution. The proposed strategy is compared with well-known production control policies widely used in literature, such as DDMRP. Simulation results demonstrate the benefits of implementing an adaptive production control as it enables the closed-loop supply chain to enhance customer service level and bullwhip effect. Additionally, a sensitivity analysis is provided to assess the influence of experimental factors on the performance. The analysis highlights the significance of return flows and manufacturing operations for the closed-loop supply chain.KEYWORDS: supply chain dynamicsdisruptionchangeoverproduction controlbullwhipDDMRP Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Università di Catania [PIACERI 2020/22 – GOSPEL / 59722022261].Notes on contributorsRoberto Rosario CorsiniRoberto Rosario Corsini, PhD, is a postdoctoral researcher in Technology and Manufacturing Systems at the University of Catania (Italy). He holds a PhD in Complex Systems for Physical, Socio-economics, and Life Sciences and a Master’s degree in Management Engineering from the University of Catania. His professional background includes roles as Production Planner and Healthcare Management Engineer. His research activities deal with the application of AI frameworks, optimization techniques, and simulation models for Manufacturing Systems, Supply Chains, and Healthcare Systems