Bullwhip Effect Study Based On APIOBPCS Policy

This dissertation investigates Bullwhip Effect and inventory variation generated in a general supply chain and emphasizes the impact of the Bullwhip on the supply chain and considers a well-established production-scheduling algorithm, called the Automatic Pipeline, Inventory and Order Based Production Control System (APIOBPCS). The introductions about the aim and implication of this research and APIOBPCS policy are made, and the types and the induced sources of the Bullwhip effect simply explained. Relevant research fields and status quo are reviewed in detail, and the main research theories, methods, measures and conclusions related to the Bullwhip effect generated in the present scholastic literatures are simply demonstrated. A transfer function model of the system through using causal loop diagrams, block diagrams, difference equations and z-transforms is built up and the stability and robustness of the APIOBPCS supply chain system via this model is discussed. It is shown that instability arising from poor design and its avoidance via the appropriate parameter settings for tuning the two feedback loops within the supply chain for a specific production delay. The procedure is readily extended for other production delays and distri-butions. From the control engineering perspective, when an analytical expression for bullwhip generated in the supply chain based on the special case of APIOBPCS model, i.e. the DE-APIOBPCS model is derived, an analytical expression for the variance of the inventory position is also derived and used together with the bullwhip expression to determine suitable ordering system designs that minimize both bullwhip and inventory variance for a range of weightings between the two variances. When order-up-to replenishment policies are used with the different forecasting methods, the bullwhip effect generated in simple supply chain is analyzed. Whereas a generic production control replenishment policy called APIOBPCS is demonstrated to avoid demand variance amplification and generates smooth ordering patterns in the supply chain. The beneficial impact of information sharing in multi-stage supply chains is discussed. With the use of OUT policies, via comparing the traditional supply chain with the information shared supply chain, it is showed that the bullwhip effect (variance amplification of ordering quantities) is reduced significantly in the latter with the help of information sharing, especially at higher levels in the chain but variance of ordering quantities still increases as one moves up the chain. When using the smoothing APIOBPCS policies, it is showed that information sharing helps to reduce order variance at the higher levels of the supply chain. This dissertation compares the expected performance of a vendor managed inventory (VMI) supply chain with a traditional "serially linked" supply chain both based on APIOBPCS. When adopting VMI, it is showed that the rationing and gaming or the Houlihan effect, and the order batching effect or the Burbidge effect may be completely eliminated, however, Forrester effect is less clear cut. VMI is significantly better at responding to volatile changes in demand such as those due to discounted ordering or price variations etc.