為了確保產品品質能長期符合消費者之需求,
如何進行一有效的篩選試驗 (Screening Procedure, 或稱預燒 (Burn-in) 測試) 以及評估產品之壽命,

是所有製造商或生產者皆要面臨之一重要決策問題。針對高可靠度產品,

若存在一與壽命具高度相關之品質特徵值 (Quality Characteristic, 簡稱 QC)

且假設該品質特性之衰變路徑服從一 Wiener 過程,

則可由成本觀點建構一套篩選試驗執行程序, 以決定最適之預燒時間。

然而當產品品質特徵值之衰變速度緩慢時, 將須要很長的預燒時間才能達到篩選良莠之目的,

因此如何利用類似 Cusum 之觀念, 整合隨機積分來達到快速分類, 以確保產品品質,

將是決策者之一大挑戰。

本論文首先利用混合 Wiener 過程來描述產品在進行預燒測試之前的衰退路徑,

接著引進積分之 Wiener 過程來計算衰變路徑的累積衰退量,

進而建構出適當判別 (分類) 準則, 得以快速篩選出產品之不良品。

最後本研究將與 Tseng \& Tang (2001) 之方法作理論上的比較分析,

詳細說明錯誤分類損失的機率及成本之差異,

並探討此兩種方法的使用時機及範圍限制。

此研究之成果可提供生產者剔除不良產品之有效篩選程序,

它將有助於廠商縮短預燒測試時間及節省試驗成本。

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