摘 要

　　面對科技的日益進步，系統設備愈來愈龐大且複雜，若一旦發生故障，將導致嚴重的傷害及損失，為維持設備在良好的運作狀態，因此適當的對系統進行預防性保養，以降低可能帶來的損害，日益受到重視。適度的預防保養可以確保系統良好的運作狀態以及提升設備可靠度，然而從經濟的角度來衡量預防保養，過於頻繁的預防保養卻會造成資源、成本的浪費以及設備使用率的降低，故在最適時間執行最適預防保養政策是設備維護的目標。以往的文獻多假設系統的壽命分配服從某種型態的分配且參數為已知常數，然而從實務上發現，系統失效分配通常為未知的或包含不確定參數，因此需要更適合的方法來精確估計這些給定分配的參數或系統的平均壽命，然而缺乏的資料數據並不足以進行傳統的統計分析，而額外的收集這些失效數據可能是非常昂貴，不符合成本效益。因此本研究主要針對隨著時間而逐漸退化的設備，假定系統元件為可維修，且系統因失效而維修的頻率服從非齊次卜瓦松程序，藉由利用貝氏決策分析模式將其分為事前分析、事後分析之前置分析以及事後分析三個階段來建構考量最小修理的預防保養模式，且在本研究的貝氏決策分析的模式中，除了考量專家意見外，為了降低資訊不明所產生的不確定性，尚須考量資料收集的必要性，所以透過事前所考量的專家意見所得之決策，與事後收集資訊後所做之決策進行比較，增加決策之精確度，以提供一個決策分析模式來幫助廠商找出做最適的預防保養策略，並藉此求得最適的預防保養執行次數，使廠商單位時間期望成本最小，最後透過實證應用分析來驗證本研究所建構出的決策模式，並做出總體的結論與建議。

Abstract

　A system will deteriorate as well as its components with age. To restore or keep the function of a repairable system in good state, preventive maintenance is often performed. Research has been studied in finding optimal preventive maintenance policies for deteriorating repairable systems. However, such a decision involves many uncertainties and the assessment of parameters is often difficult due to scarcity of data. It is therefore important to make use of all information in an efficient way. For instance, prior knowledge is often importance and can conveniently be incorporated by the Bayesian approach. In this paper, a Bayesian decision model is developed to determine the optimal number of preventive maintenance for systems maintained according to a periodic preventive maintenance policy. It is assumed that the status of the system after preventive maintenance is somewhere between as good as new for perfect repair and as good as old for imperfect repair. For failures between two preventive maintenances, the system undergoes minimal repair, and after each minimal repair, the system resumes its function as good as old. A preventive maintenance action will improve the health condition of the system and therefore reduces the effective age. A nonhomogeneous Poisson process with a power law failure intensity function is used to describe the behavior of the deteriorating repairable system. This research focuses on the study of finding the optimal number of preventive maintenance by minimizing the expected cost rate for the deteriorating system with minimal repair at each failure. Finally, a numerical example is given and the results of the preventive maintenance model are discussed by presenting the sensitive analysis.

參考文獻

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陳耀茂，民89，「機率過程導論」，五南，臺北市

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