Simulation of an Inventory Policy Based on the Demand Driven MRP Methodology from a Petri Nets Approach

Abstract

Context: Currently, companies are facing a problem associated with inventory control since there is a high number of references that they must manage to reduce lost sales and minimize low-turnover inventory. Method: Demand Driven MRP (DDMRP) is an innovative inventory control strategy that incorporates elements of Lean systems and theory of constraints which lead to the introduction of dynamic buffers with the purpose of controlling inventory levels while responding to the demand. Petri nets are used to simulate and validate the application of the DDMRP methodology in a finished product inventory. Results: From the conducted simulation, it is possible to verify the effectiveness of the DDMRP methodology for the case under study, where the overstock is reduced while the possibility of out-of-stock is minimized. Conclusions: The simulation of the DDMRP methodology through Petri nets allowed evaluating the performance of the policy before its implementation with the purpose of validating the effectiveness of the strategy on company performance indicators such as the level of service and costs storage.