Enhancing Agility of Supply Chains Using Stochastic, Discrete Event and Physical Simulation Models

Managing supply chains in today’s distributed manufacturing environment has become more complex. To remain competitive in today’s global marketplace, organizations must streamline their supply chains. The practice of coordinating the design, procurement, flow of goods, services, information and finances, from raw material flows to parts supplier to manufacturer to distributor to retailer and finally to consumer requires synchronized planning and execution. Efficient and effective supply chain management assists an organization in getting the right goods and services to the place needed at the right time, in the proper quantity and at acceptable cost. Managing this process involves developing and overseeing relationships with suppliers and customers, controlling inventory, and forecasting demand, all requiring constant feedback from every link in the chain. First, a survey of existing stochastic models is presented. Base Stock Model and Q (r) models are applied to three tier single-product supply chains to calculate order quantities and reorder point at various locations within the supply chain. A computer based discrete event simulation model is created to study the three tier supply chain and to validate the results from the stochastic models. Results indicate that agility of supply chains can be enhanced by using the stochastic models to calculate order quantities and reorder points. In addition to reducing the total cost of inventory, probability of backorder and customer dissatisfaction is minimized. Results are further validated with physical simulations. Both computer based simulation and physical simulation demonstrate the improvement in the agility of the supply chain with reduced cost for inventory.