本研究主要目的是解決CNC機器之預防維修排程問題(Preventive Maintenance)，預防維修問題則是在機器排定各項工作行程之時，插入預先維修的行程以降低機器設備損壞所造成的額外維修成本，目標則是要求出擁有最短完成時間的排程最佳解或近似最佳解，而解是由以下三項決策變數所組成。
1.機器速率
2.工作排程(Scheduling)
3.預先維修排程(Preventive Maintenance decisions)
機器速率為可調整參數，速率越高使機器刀具負擔更大，損壞機率也因此提高，也就更需要排定預防維修以降低刀具損壞機率。

工作時間、損壞機率、機器刀具修復時間及工作準備時間為隨機，不適用一般統計數學方法求解，所以本研究採用模擬最佳化(Optimization via Simulation)之方式求解，結合修改至適合隨機問題的基因演算法(GA)及模擬退火法(SA)，並利用排序與選擇程序(Ranking and Selection; R&S)來決定其中之最佳解。

最後在實驗過程可以觀察到，加入R&S不論是在GA或是GA+SA上均可以有效提升最佳解之品質優良及穩定程度，而在面對啟發式演算法需跑多次世代求解，也就是問題複雜度較高的情況下，加入R&S對於降低樣本數及花費時間上也有著顯著的效果。但本研究尚未加入變異數減免技術來減少樣本數的使用及提昇效率，而針對問題也只為簡單的單機排程問題，所以此兩項為未來可修改發展的方向。

The purpose of this study is to solve the Preventive Maintenance(PM) scheduling problem on a CNC machine. The machine breaks down will have additional cost to repair it and insert a PM can decrease the cost.Our purpose is to find the best solution that is defined by the shortest total completion time. Each solution is characterized by different machine rate ,scheduling and PM decisions.Higher machine rate will have higher probability to break down so we need insert a PM to decrease the probability.

In our research , the work process time , probability of break down , Repair time and setup time are stochastic variables so we use Optimization via Simulation to solve this problem. So I combine the Modified Heuristic algorithm with Ranking and Selection(R&S) to find the best solution.

Finally , we found combining the R&S with GA or GA + SA can improve and Stabilize the quality of the best solution. When Facing the situation of complicated problems , heuristic algorithms have to run more generation to decide the best solution.It may cost many samples and time , but combing R&S can decrease the samples and time. We can apply VRT on the procedure to decrease the samples and time or use this procedure on more complicated problems in the future.

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