An Adaptive Distributed Simulation Framework for a Server Fulfillment Supply Chain

Supply chains that produce and distribute computer servers are globally dispersed and have a high degree of uncertainty. To excel at servicing customers, a supplier must be highly skilled in matching the assets in the system with customer demand. Discrete event simulation has been proven valuable for system state estimation of supply chains. However, irregularities and disruptions occurring at any site along the system and the resulting bullwhip effects can lead to significant departures of simulation-based estimation from the performance of the real system. These departures reduce the ability of the model to assist in making correct decisions. In this paper, we propose an adaptive distributed simulation framework for a server fulfillment supply chain, and a Kalman filter to improve our estimates of job completion times.