The Application of Supply Chain Digital Twin to Measure Optimal Inventory Policy
Pratik Maheshwari, Suchet Kamble
Abstract
The present heterogeneous behaviour of the competitive market poses significant problems at regional as well as global scales in terms of inconsistent tracking, ripple effects, dashboard collaboration, and complex product portfolios along with stringent criteria. Meanwhile, it is also counterproductive to the visibility of the supply chain besides that adversely responsible for optimal inventory policies (OIP). Henceforth, this paper considers the supply chain digital twin (SCDT) for OIP within an integrated physical and digital world fusion vision. Consequently, the agent-based simulation method is applied to create administrative asset shells for small and medium-scale factories. The proposed model incorporates an OIP trade-off for retailers, wholesalers, customers, and factories. The results underlined the benefits and characterized OIP tactics that help estimate system performance. Finally, the managerial implications provide insides for predictive and reactive decisions to ensure the optimal supply chain running cost and customer satisfaction by utilizing the advantages of SCDT. Furthermore, this paper discusses the OIP optimization method and essential measures for developing the SCDT distribution strategy within the trade network.