在連續性生產模式的製程中，生產設備的可靠與穩定性關係著產品的品質狀況，因此設備的維護保養工作相當的重要。若能在最適切的時間點進行設備保養，將可以維持設備穩定性、延長設備使用壽命，更可以降低相關品質成本。因此，有許多學者求解預防性保養適切時機，可以讓執行預防性保養的程序能夠更有效及確實。
假設機台設備的狀況由可控狀態轉換成不可控是可以由許因子來解釋及反應的，羅吉斯迴歸模型可以用來分類預測出設備失效的概率，提供設備是否將會產生異常的警示，讓相關設備維護保養單位進行預防保養時機決策使用。
本研究使用八個機台的製程檢測資料導入模型進行分類，二分類羅吉斯迴歸模型分類的結果正確率在0.93到0.98之間。表示可以利用此二分類羅吉斯迴歸模型分類出機台可能發生異常狀態，提供給機台維修保養的單位進行預防性機台保養維護工作的參考。

In a continuous manufacturing process, the reliability and stability of machines is very critical to the quality of products. Many studies therefore investigate the period of preventive maintenance to enhance the reliability of continuous manufacturing processes. The state of a machine is assumed to be either under-control or out-of-control. The binary logistic regression can be used not only to predict the state of a machine, but also to find the critical factors for machines to be out-of-control.
In this study, a continuous manufacturing process is assumed to be supervised by three shifts in one day, and every shift will collect inspection data from the products of the process. The statistics calculated from the inspection data obtained from the previous two shifts for a machine are employed to generate a binary linear regression model to predict whether the machine will be under-control in current shift.
The experimental results on eight data sets show that the prediction accuracy of the binary linear regression model built by our method is between 0.93 and 0.98. The variance and the error rate of the inspection data obtained from the previous two shifts are the most important factors in identifying whether a machine is under-control or out-of-control.

中文
鍾明鴻，設備管理-設備管理活動之理論基礎，運用步驟與保養推展-超越企管顧問股份有限公司，民國86年。
鄭達才，設備維護管理現在與未來，中國生產力出版，民國89年。
王濟川，郭志剛，Logistic迴歸模型-方法及應用，五南出版，民國92年。

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