摘 要
本論文針對設備裝置有多個敏銳偵測儀器提出所謂之動態預防保養政策：透過偵測儀器可以於每個偵測時間點nd, n=0,1,2,3,…即時偵測設備的多個不同偵測參數數值，透過電腦中心可即時求算出設備之健康指標(Health Index，簡稱 H )而該H值可對應到一設備之狀態，並將該設備狀態值儲存於系統資料庫內，依據在nd時刻之設備狀態，以每個循環的總保養成本最低之原則，於該nd時刻決定出該採取之最佳保養動作。

本論文透過即時之H數值可判斷出設備狀態，且設備各個狀態下有多種保養動作可供選擇執行。本論文需假設設備之狀態轉換機率為一固定轉換機率矩陣，即設備之狀態轉換 為馬可夫鏈。依據不斷更新之設備運轉資料可估算出即時的設備狀態轉換機率及各保養動作的風險率，因此設備狀態轉換機率隨時更新。

具體言之，本保養策略與其他(偵測環境下)預防保養策略不同的地方在於本策略為一隨時間變動的動態保養策略，而非不隨時間變動的保養策略，且由於設備狀態轉換機率隨時更新，因此設備的轉換機率實際非為一固定值，此亦是一般企業可透過設備的歷史資料建構出隨時間變動的狀態轉換機率而搭配本保養策略，則可產生一實用的保養策略。

關鍵字：健康指標(Health Index)、多種保養動作(Multiaction)、動態保養策略。

Abstract
The purpose of this dissertation provides a dynamic preventive maintenance policy for the equipment inspected by sensors. The sensors can inspect several parameters of the equipment which can be generate a Health Index (H) in real time at each inspecting time nd, n=0,1,2,3…The H will be translated into equipment status and saved in the system database. According to the equipment status, we can decide the best preventive actions at time nd by the rule of the lowest total maintenance cost per cycle.

The state of the equipment can be charge by H. Each state of the equipment has several preventive actions to choose. We suppose the state transition probability of the equipment as a steady state transition probability matrix, which means the state of the equipment is a Markov chain. Base on continuing updated H value, we can estimate the state transition probability of the equipment and the risk rate of each preventive action at every nd n=0,1,2,3…. As a result, the state transition probability of the equipment will be updated with nd.

In brief, the major differences between this preventative policy and others are that this one policy is updated by time and the state transition probability of the equipment can be updated by time. Therefore, the enterprise can base on the equipment historical data to generate the updated transition probability with time, and follow the methodology as we mention above then it can build up an useful maintenance policy.

Key word: Health index, Multiaction, Dynamic maintenance policy.

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