A Change-point Control Chart Approach For Supply Chain Process Quality Control

With the development of globalization, the competition between supply chains has become the main mode of marketing competition. In supply chain context, the connection between business process is the key factor for supply chain operation. Enterprises have changed their focus from product to process. From a process perspective, this dissertation views the supply chain process as a serial or serial-parallel process to explore the quality control along supply chain.Variation is the root cause of quality problem in quality engineering discipline. Due to the unshared structure of information, the variation which transmits through the entire supply chain is probably to be magnified, which may cause the supply chain operation out-of-control. Thus, it is necessary to reduce and control the variation in each stage within supply chain to guarantee the normal operation. Statistical process control (SPC) technology can reveal the potential failure to ensure the normal operation of the supply chain process. Therefore, it has important theoretical and application value to adopt SPC technology to monitor supply chain system. Control charts are the common tools for SPC. Furthermore, a change-point control chart can trace the true moment that a process changed, then realize a quickly quality diagnosis. Therefore, this dissertation adopts change-point control chart to monitor and diagnose supply chain process from the perspective of reducing and controlling variation. Integrating state space modeling and simulation method, this dissertation systematically studies the quality control of different supply chain process, serial and serial-parallel process. The main research contents list in the following:(1) As for serial process, with the use of state-space equation to model supply chain process, this dissertation adopts a change-point chart based on direction information to monitor supply chain process and then analyze the performance. A case analysis and a sensitivity analysis are illustrated to verify the effectiveness and robustness of the approach. Results indicate that the change-point control chart has great performance both in monitoring and diagnosis.(2) As for serial-parallel process, based on the case of serial process of supply chain, this dissertation sets two workstations in the sub-process that costs long time to found a serial-parallel process. Considering the difference of variation propagation, dumb variables are added to state-space equation to model process. Then, a change-point chart is used to monitor supply chain serial-parallel process. Then we analyze the performance of the change-point control chart. Finally, a sensitivity analysis is illustrated to verify the robustness of this approach. Results indicate that the change-point control chart can effectively detect the stage and variables that have changed and distinguish the cause of the abnormal variation from mean and variance.On the basis of the above research results, this dissertation also discusses some challenging topics which deserve further research in the future.