台灣在進入工業時代後以製造業為重,然而近年來台灣傳統產業面臨生產成本日益升高、勞工短缺及環保意識迅速發展等挑戰,因此對於台灣的製造業該如何在生產過程中減少過多的閒置與浪費,達到低成本高生產率是個重要課題。故本研究是以汽車製造業之多人生產線平衡問題作為探討對象,且多人生產線與傳統產線的最大不同在於工作站中操作人員配置數量。因此本研究將透過建構一套最佳化數學規劃模型,以最小化工作站數及操作人員配置數為目標,並進行相關決策分析以達到最佳配置及效率。透過田口方法的實驗設計,利用不同大小問題驗證本研究之免疫遺傳演算法的正確性後,針對結合案例公司的問題,運用免疫遺傳演算法求解,並與最佳化軟體求得之解做比較,最後針對可能影響之參數做敏感度分析。
Manufacturing business has the been key point ever since Taiwan enters industrial era. However, challenges like, the growing manufacturing cost, the emerging labor shortage and the rising environmental awareness are putting traditional industry in a even more difficult situation. How to reduce excessive wastes and achieve low-cost and high-efficiency during production have become an important topic for the industry. This research will focus on how to find the problem of balancing production lines with multi-manned workstations in Car industry. The major difference between these issues and the balancing of traditional production line is the allocation of manpower at the workstation. This research is focusing on building a optimal mathematic model to minimize the number of workstations and manpower allocation and perform the correlation between efficiency and manpower distribution. Also, using Taguchi methods, we have done different scale of experiments to prove the validity of our Immune Genetic Algorithm. After validation, we have demonstrated our Immune Genetic Algorithm by conducting experiments on cooperated company data, and compared the result with the other optimization software. In the end, we can do sensitivity correlation of possible factors by previous results.