在此研究中我們假設機台的狀態有兩種，而狀態的衰退速率會依據當前的工作條件有所差異。我們希望利用 Cox 比例風險模型透過機台的工作條件、環境資訊估計各個狀態的失效率，並利用其結果估計馬可夫決策過程中的轉移機率。藉由機台資料即時的更新調整維修計畫，降低維修、營運的成本。;In today’s automated and mass-produced manufacturing industry, the issue of machine maintenance continues to attract people’s attention. It is very difficult for managers to formulate maintenance strategies. The information about machines is diversity. In the research of machine maintenance, the Markov Decision Process is often used as a model to discuss the planning of maintenance time, the decision-making of maintenance actions is made in a fixed time period, and the long-term optimal maintenance solution is obtained by dynamic programming. We want that managers can estimate the deterioration rate and transition probability in real time based on the information of the machine.
We want to use the Cox proportional hazard model to estimate the failure rate of the machine through the working conditions and environmental information. Using the results to estimate the transition probability in the Markov Decision Process, and determine the maintenance policy. By updating information to adjust the maintenance plan in real time, the cost of maintenance and operation can be reduced.
