The Study on the Production Scheduling Problems for IC Burn-in Test Factories

• Main Author: 洪志勳
• Other Authors: 彭文理
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/74492096073047617943

博士 === 國立交通大學 === 工業工程與管理學系 === 101 === To be competitive, the semiconductor industry companies need to utilize their capacity and to satisfy customers’ due dates in order to increase their profitability. In the final stage of IC testing process, the burn-in test is the key process to ensure the reliability of out-going ICs; the burn-in process usually causes bottleneck in production because the burn-in time is long, and its schedule mainly affect the system performance of IC test factories. Therefore, an essential scheduling problem is tackled for the bottleneck operation. The burn-in test scheduling problem (BTSP) is complicated because it is a multi-dimensional problem, involves the constraints of different product group, unequal ready times, non-identical job sizes, limited machine capacity, and batch dependent processing times. Therefore, the development of efficient algorithms is critical to form appropriate batches and to arrange a suitable schedule for those jobs which have been processed by the IC testing operation. For the BTSP, jobs are clustered by their product groups, while the test time of jobs in same group may different according to their product family. Jobs in different product family of same product group could be processed in a batch and the process time will be the longest process time of product family of the batch. In addition, the capacity of burn-in machines may different due to different machine brand or models. Furthermore, setup times for two consecutive jobs between different product types on the same machines are sequence-dependent. The burn-in test is a high energy consuming operation, how to use minimal machine time to complete all jobs is the key to manage the cost. Consequently, the objective of BTSP is minimal workload. In this dissertation, we considered identical parallel machine and non-identical parallel machine scheduling, called iBTSP and nBTSP. We formulated iBTSP and nBTSP as two mixed integer linear programming models (MILP). For the iBTSP, it can be viewed as a multi-level optimization problem, the sub-problem can be transformed into the vehicle routing problem with time window (VRPTW), a well-known network routing problem which has been investigated extensively. We present two compound algorithms based on the network algorithms with some modifications to accommodate the iBTSP and the computational results and performance comparisons show that the proposed algorithms are efficient and near-optimal. We analyzed the problem size and the computation time of the nBTSP, and found the total job number and machine number impacts the computation time most.