本研究利用機台健康資訊,發展即時動態派工與預防保養策略,其能有效應用於小規模非等效平行機台製造系統。有許多原因會造成機台的健康程度不同,其一正是因為機台的老舊程度,或磨耗程度,造成各機台對同種產品的處理速度不一致,故本研究將因機台健康程度不同而有不同加工速率的狀況定義為一非等效平行機台問題。在此生產環境下,若沒有考量到機台健康資訊並搭配妥善的派工策略,將造成產能不平衡、生產週期時間過長,進而導致系統生產成本增加,這些都是進行動態派工的動機,更能應用於預防保養策略。 本研究利用動態規劃(dynamic programming)建立多產品多機台的動態派工與預防保養策略模型(Dynamic Dispatching with Preventive Maintenance Model,DDPM Model),目標為最小化等候成本,並針對小規模兩產品兩機台系統撰寫程式求解,再進行數值範例分析及模擬驗證。最後以離散事件模擬(discrete event simulation)對小規模兩產品兩機台系統DDPM模型進行驗證,與其他傳統派工方法比較,結果顯示DDPM能有效提升系統平均製造率且降低總等候成本。
This study uses machine health information to develop an efficient dynamic dispatching and preventive maintenance policy for inequivalent parallel machines. Inequivalent parallel machines have similar function and can process the same group of products, but the production rates could be different. In many industries, the difference of production rates between inequivalent machines is caused by deterioration of machines over time. When production rates are different among inequivalent machines between different products, a proper dispatching strategy is critical for reducing production cycle. In addition, this study also integrates preventive maintenance policy into dynamic dispatching model so as to save more waiting cost. The Dynamic Dispatching with Preventive Maintenance Model (DDPM Model) is developed and formulated with stochastic dynamic programming. The model objective is to minimize the total waiting cost. Finally, the discrete event simulation is used to verify the DDPM model of two-product and two-machine system. Compared with several traditional dispatching rules, DDPM can effectively increase average production rate and also decrease total waiting cost.