Abstract
The function of WIP for different workstations of a semiconductor manufacturing system is analyzed, the required total WIP level of the system is estimated by using the neural networks, and then the total number of WIP is allocated to each workstation and operation by using the queuing theory to achieve the best overall throughput performance. The resulting WIP level for each workstation is then used to control the manufacturing system. Based on the difference between the planned and the actual WIP levels of different machines, an efficient control method is then developed to maintain robustness of the system.The simulation result shown that the proposed method for allocating total WIP to workstations and operations can reduce 16% of mean cycle time and not increase the variation of cycle time in this manufacturing system.