Predictive control strategy of discrete supply chain system under networked manufacturing

Minimum variance control was proposed for high uncertainty of customer demand in discrete supply chain system. Relative to traditional predictive control strategy, this approach is fit for tracking demand variations, and reducing or eliminating 'bullwhip effect'. The entire chain could be modeled by combining each unit transfer function with z-transform into a close loop transfer function for the network. Customer demand trends were described by a general auto-regressive integrated moving model, and the customer demand forecast was used to determine two inventory target levels. The objective function based on ordering policy was established, and minimum variance predictor was used to handle the customer demand. The performance index function and the analytical equation for the bullwhip effect were proposed, and two control parameters were used to regulate the excess inventory and backorder in minimum variance controller. The feasibility and validity of this approach which forecasts the changes in the market, track customer demand, and maintain a proper inventory level were shown by the simulation results.