近年來隨著科技進步與製程提升，消費者對產品品質與可靠度的要求日益提高。高可靠度產品需兼顧快速上市與壽命保證的要求，使得預燒試驗投入大量的時間和成本。因此，如何在兼顧品質保障與經濟效益的前提下，進行高效率的預燒試驗來評估產品壽命，已然成為製造商們的重要課題。高可靠度產品的預燒方法可以透過一個與產品壽命高度相關的品質特徵(Quality Characteristic, QC)衰退量來進行，透過觀察該品質特徵的衰退資料來建構衰退模型，可以快速獲取產品壽命資訊。以衰退模型來評估高可靠度產品之壽命資訊，已被廣泛應用於壽命預測與可靠度分析相關研究中，然而過往研究大多都對於衰退模型進行同質變異數假設，但此假設無法真實地反映產品衰退過程。在本研究中，以Tseng et al. (2003)與蕭裕翰 (2024)的研究為發展，以Wiener過程構建品質特徵的衰退模型，結合考量衰退路徑值與衰退增量變異二者下，透過在判別分析中以最小化期望判別錯誤成本為分類法則，求取最佳分類切點組來作為辨別正常與瑕疵產品的準則，並綜合考量錯誤判別成本與試驗量測成本，以決定最佳的預燒時間點。案例分析中，Meeker and Escobar (1998)中的雷射設備資料作為個案，以操作電流增量比作為品質特徵來說明本研究判別方法的分類過程並討論試驗量測成本對最佳預燒時間點之敏感度影響。

With the advancement of manufacturing processes, consumer expectations for product reliability have been increasing. Under the premise of ensuring both quality assurance and economic efficiency, how to evaluate the lifetime of high-reliability products through burn-in testing has become a significant issue for manufacturers. Constructing a degradation model based on the degradation values of a quality characteristic (QC) that is highly correlated with product lifetime, known as an accelerated degradation test (ADT), provides an efficient approach to obtaining lifetime information. In previous related studies, the degradation models were mostly built under the assumption of homoscedasticity, which may not realistically reflect the actual degradation process. This study, building upon the works of Tseng et al. (2003) and Hsiao (2024), integrates both the degradation path value and incremental variance differences. By applying Discriminant Analysis with the minimization of expected cost of misclassification as the classification rule, an optimal set of classification thresholds is derived, along with a burn-in time that minimizes the total cost. The laser device data from Meeker and Escobar (1998) is adopted as a case study to illustrate the classification procedure of the proposed method and to discuss the sensitivity of the optimal burn-in time with respect to measurement and testing costs.

中文文獻：
蕭裕翰（2024）。應用判別分析探討高可靠度產品之預燒試驗分類決策。﹝碩士論文。國立成功大學﹞臺灣博碩士論文知識加值系統。https://hdl.handle.net/11296/92rd63
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