整合批量分割與人力資源之彈性開放式生產排程-以工具機主軸加工業為例

Abstract

本研究探討在考慮批量分割情境下，同時兼顧機台與人力技術水平的彈性開放式排程問題。在工具機主軸加工產業中，隨著現場逐漸採用高精度機台設備，機台的設定需具備專業技術與程式能力的人員進行操作。由於各機台的設定方式不同，人力技術水平成為影響排程的重要因素。此外，該產業製程間轉換的原物料體積龐大，加上每位客戶訂單數量不同，使得單筆訂單難以在同一時間內完成所有製程後統一移送至下一站。因此，本研究納入批量分割，允許訂單部分批次完成後即先行投入下一道加工製程，藉此縮短整體生產週期，提升生產效率與產能。為貼近實際生產情境，本研究更進一步考量機台維修時間，以及生產進行到一半時可能存在指定機台和已完工量之限制。 在上述條件限制下，由於該產業於生產過程中通常考量機台稼動率和準時交貨予客戶的表現，因此本研究設定之目標為最小化總延遲時間和總完工時間，並分別給予權重參數w_1和w_2。為有效求解此複雜排程問題，將使用混合整數規劃模型與啟發式演算法進行分析，透過比較兩種方法於不同規模、參數設定及交期條件下的求解表現，探討其優劣性與適用範圍，以解決加工廠之實務情境問題。

This study examines an open shop scheduling problem that includes batch splitting, flexible use of machines, and operator skill levels. In the machine tool spindle machining industry, high-precision equipment requires setups by workers with specialized technical knowledge and programming skills. Because machine setups differ, operator skill becomes an important factor in scheduling. Additionally, large volumes of raw materials and varying customer order sizes make it difficult to complete all processes of an order simultaneously before moving to the next stage. Batch splitting is introduced to allow parts of an order to move to the next process once completed, reducing overall production time and improving efficiency and output. To better represent real-world situations, this study also considers machine maintenance schedules and practical constraints, such as specific machine assignments and partially completed orders. Since the industry values high machine usage and timely deliveries, the study aims to minimize total tardiness and total completion time, and I use w_1 and w_2 to represent the weight parameters separately. To solve this scheduling problem effectively, the research uses both a mixed-integer programming model and a heuristic algorithm. By comparing the two methods under various conditions and delivery requirements, this study evaluates their performance and suitability for real machining workshop environments.