運用資料探勘技術探索國軍輪車維修策略之研究

隨著科技的進步，車輛發展日益複雜，性能及技術不斷精進，除購買成本高昂外，更增加操作、維護的複雜度，當車輛運作異常時，會造成任務延宕或人員傷亡，其花費之人力、物力、費用相對提高，且會耽誤任務執行是否順遂。因此，運用資料探勘技術，規劃一套最適預防保養維修策略，以提升車輛維護績效。維修策略因應不同裝備型式或維修成本考量的因素不同，相對採取的預防保養作為也不相同。因此，運用資料探勘技術，將歷年維修資料分析出精進維修策略之具體做法，並使維修金額有更客觀的分級制度，在各系統預防保養作業下，找出最重要之預防保養項目及重點，以期達到總成本最小化之目標，並且降低事故發生機率。本研究所提出的維修金額分級模式應用於預算編列上，提升匡列預算額度的準確度，降低維修總成本，並預防事故發生，進而確保戰力的發揮。

關鍵字

維修策略；資料探勘；決策樹；關聯法則；群集分析

並列摘要

With the technological progression, the development of vehicles is getting more elaborate, and the performance and technology continue to be improved. Besides the extremely high cost, it is harder to operate and maintain a vehicle. When there is malfunction happening, it may delay missions or cause deaths or injuries. Then, much more labor, material resources and expenses will lift up the cost; moreover, it can affect the efficiency and effectiveness to do tasks. Thus, we should have data mining techniques applied to set up a series of strategies for prevention, maintenance and restoration in order that the performance of vehicle maintenance will surge. Based on diverse models or cost consideration for repairing, there would be different preventive maintenances applied correspondingly. Putting data mining techniques into use is able to analyze historical data and then specify what are the better maintenance strategies. Also, to have a more objective rating system of maintenance charges leads to find the most critical preventive maintenance items and focuses under varied systems of preventive maintenance so as to meet the goal of minimizing the total cost and to downsize the occurring rate of incidents. Applying the model of grading maintenance charges proposed by our institute to budget planning can increase the accuracy when designing budget, decrease total maintenance costs yet prevent incidents in order to assure the military performance.