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工業技術研究院

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具校正成本最適化之製程缺陷成因分析技術

技術簡介

產品規格超出標準時,即便利用(串)製程分析,搭配SPC的製程管制統計分析,現場製程工程師仍難以快速探索出影響產品品質變異的多個參數(組),而統計式分析只能針對定量(數值型)資料分析,當製品瑕疵變異成因/屬性多樣化時,現有解決方案無法協助專家進行相關分析,並找出校正規則。

特色與創新

製程缺陷成因分析技術具異質資料前處理機制,可分析混和數值型與非數值型參數之製程資料,並採用Logistic Regression、Random Forest、SVM(Support Vector Machine)、Decision Tree為基礎建立多種成因分析模型。同時,具成因貢獻度統合機制,可統合各成因分析模型之分析結果,提供複合式異常因子貢獻度排序。提供製造現場缺陷成因分析及校正建議,縮短良率學習時間。目標規格為相對良率提升率>50% (相對良率提升率=校正成功之缺陷資料數/缺陷資料總數)。

具校正成本最適化之製程缺陷成因分析技術
具校正成本最適化之製程缺陷成因分析技術



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