近年由於大陸鋼廠崛起，挾著規模經濟採取多量少樣的生產方式，以價格及產量優勢搶占大量市場；台灣鋼廠之規模雖然無法與其相比，但在技術與品質仍有其優勢，從多量少樣計劃生產方式轉為多樣少量的訂單生產方式。為了符合客製化的訂單生產，必須滿足客戶品質、訂單交期及零庫存的要求，然而製程加工時通常會產生瑕疵品，為要趕上訂單交期必須以重工方式修復瑕疵，因此可能影響原先生產計劃的時間安排，進而造成其它訂單的生產延遲。
本研究擬探討盤元與直棒製程中經常處理之平行機台工件重工排程問題，在考慮交期與整備時間下，依平行機台生產條件限制，決定各工件應在哪一平行機台之排程順序，再假設各平行機台產生瑕疵工件之比例為已知下，決定重工工件應於哪一平行機台之排程順序。利用貪婪演算法ARI (All Reworks Insertion Rule) 和SRI (Single Rework Insertion Rule ) 二種不同角度的法則，以單一製程為試算單位，計算出原工件的生產排序與重工工件的插入排序，來求解區域的最佳解以達到全域的最佳近似解，並以禁忌搜尋法求解全域的最佳近似解，推算符合現場實際生產狀況的排程完成時間，提昇客戶訂單的達交率，以達到最小化平行機台中之最晚完工時間為目標。
在求解效率與品質的表現方面，SRI較ARI為佳；由於ARI在交期、檢驗時間與工件有長短工時幾種因素影響下，其總完工時間數據的起伏變化較大，若將ARI經禁忌搜尋法進一步改善後，其表現將大為改善，在鋼鐵業的直棒製程中，運用SRI與ARI的運算結果可優於現行既有的排程方式。

China’s steel mills have been a major player in the market because it follows a high-volume-low-variety strategy. This strategy involves selling large quantities but just a few types of steel in order to maximize production efficiency, which keeps prices low. High efficiency and low prices are China's primary advantages in the market. Even though the economic scale of Taiwan’s steel mills is smaller than China’s, Taiwan’s technology and quality of the steel are still competitive in the market. Hence, Taiwan’s production model has changed to a make-to-order strategy, meaning Taiwan produces a large number of customized steel products but low volumes of each type. In order to satisfy the customized specifications by different clients, steel mills have to fulfill different requirements on steel quality, deadlines, and zero stock. Because each customized steel product usually requires its own manufacturing process, defective products are common. Steel mills have to fix defects and rework their manufacturing process in order to meet deadlines of orders. Therefore, the reworking process may affect manufacturing schedules, which will in turn delay manufacturing of other orders.
This thesis discusses issues of rescheduling jobs on parallel machines under steel bar manufacturing process. Due-dates, setup times, and production limitations of parallel machines can be used to determine individual work in a certain order for parallel machine scheduling. Furthermore, assuming that the rate of defective products of each parallel machine are known, one can reorganize tasks in a certain order to optimize the output of using parallel machines. In order to efficiently calculate good manufacturing schedules, we propose greedy algorithms based on two rules: ARI (All Reworks Insertion Rule) and SRI (Single Rework Insertion Rule). Once the original orders and the new order are known, these data can be used to calculate good local optimal solutions, which can then be further improved. We also give a tabu search method to solve our problem. By our proposed solution methods, steel mills could increase more production with shorter completion time of parallel machines.
Our computational experiments indicate SRI performs better than ARI. However, the performance of ARI could be much improved when it integrates with the Tabu search mechanism. Both SRI and ARI are useful for making better schedules for manufacturing steel bar.

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