PCB產業智慧檢測需求發酵 AOI辨識藉AI優化成趨勢
Date: 2018-07-23
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自動光學檢測(Automatic Optical Inspection;AOI ) 是以非接觸的方式,運用機器視覺技術擷取影像進行分析,進而判斷半成品是否存在瑕疵,為業界廣泛應用的檢測手法。
由於部分產業如印刷電路板(PCB)在極高良率的要求下,AOI設備容易因敏感而出現過篩現象,因此產業在需要更智能化的檢測系統條件下,開始應用AI技術來輔助AOI設備進行後續篩檢的優化。
以PCB產業為例,AOI檢測系統流程主要係先利用光學儀器對待檢測的PCB板進行掃描獲取圖像,然後系統對數據庫中的合格參數進行比對,經過計算機圖像處理技術檢查出PCB上是否存在缺陷,可檢測的缺陷種類包括短路、多銅及少銅、斷路、缺口、毛刺、銅渣、缺件、偏斜等。
但業界指出,目前AOI檢測會面臨過度篩檢的現象。造成此現象的原因一來是因PCB產業有高良率的要求,因此在AOI的參數上設定非常嚴格。二來則是因光學原理容易使AOI因光影干擾而敏感,因此只要有些微外在光影的影響,設備便會自動判讀為缺陷品。
經業界統計,當PCB產業使用AOI設備進行檢測時,過篩的機率高達70%,因此目前產業的作法是採取人工進行第二次篩選,將實際合格的PCB板再度送回產線,估一台AOI檢測機常需配置4名人員進行再篩。
為降低不必要的人力消耗並加快產線檢測速度,目前PCB產業正嘗試導入AI辨識模塊,利用視覺辨識技術輔助AOI檢測的後續優化,以提高檢測設備的辨識正確率。 PCB業者預估導入AI視覺辨識後,將可有效降低過篩機率至25%。而AOI檢測與AI辨識的差異,在於是否可針對未知瑕疵進行識別。 (新聞來源:DIGITIMES)
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