Increasing the Efficiency and Effectiveness of Inventory Management by Optimizing Supply Chain through Enterprise Resource Planning Technology

Abstract

Good inventory administration is an important task in the management of the supply chain of any business. Effective inventory handling practices aim to reduce the cost of procurement by effectively managing and optimizing inventory, so that supply chain (SC) members are not affected by surplus and deficit. By proper demand management, material requirement planning, sourcing, procurement, receive and issue, we can optimize our inventory and increase the efficiency of supply chain management. To optimize inventory, we have to control and manage running stock, excess stock, old stock, and dead stock. ERP can help us to integrate all the processes (Demand, Material Requirement Planning, Sourcing, Procurement, Receive, Transfer, Issue, Adjustment, ABC Analysis, FIFO Method, Safety Stock, Stock Management) and optimize the inventory. In this paper, we propose an Inventory Optimization and Cost Saving Model and also a method that effectively uses a Genetic Algorithm (GA) for better control of inventory and increase the efficiency of the supply chain. This paper reports on a genetic-based approach to improving inventory management systems in the asset management of the industry. This paper targets specifically the quantification of the maximum level of stock and the level of deficit required for the asset's efficiency in the transaction list so that transaction costs can be reduced. The method is used in a three-phase delivery model that is trained to perform well. I guess that we can remove the bullwhip effect and constraints by optimizing inventory by using ERP.