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工業技術研究院

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複合式在製品缺陷分類技術

技術簡介

生產檢測是製程重要的一環,代表出貨產品的品質與公司信譽,因此產品全檢是所有企業要求的目標。然為節省成本及時間,目前業界採取抽檢之方式來進行品質監測,但如此並無法達到全方位品管。特別是傳統製造現場因人工分析,更不易判別。

特色與創新

導入複合式在製品缺陷分類技術,可處理更多參數種類、結合更多分類技術、提升判別正確率,進行即時檢測產品的品質與良率,出現不良品可即時停機檢查。協助現場人員即時掌握在製品品質狀況,以防杜廢品進入下一製造程序而產生之二次損失。

複合式在製品缺陷分類技術採用Logistic Regression、Random Forest、SVM (Support Vector Machine)為基礎,建立多重缺陷類別分類技術,可再擴充機率式及NN(Neural Network)等分類器。並具幾何平均式統合、Top 2信心度複合式統合方式計算複合式的判斷結果。可分析參數≧50種,缺陷類別≧5種,並提供判別信心度。並考量缺陷資料特性多樣化,以多專家系統方式建立分類模組,利用Bagging及Boosting方式對訓練資料及參數維度重新取樣,具綜合類別偵測信心度評估機制,提供分類器效能不同加權方式。

圖解複合式在製品缺陷分類技術
圖解複合式在製品缺陷分類技術



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