應用資料探勘技術偵測汽車Robot噴塗設備異常狀態－以K廠為例

Research on Application of Data Mining to Anomalistic Operation of Robot Spraying Equipment-An Example of "K" factory

周建中(Chien-Chung Chou)

指導教授 ： 龐金宗

元智大學/資訊學院/資訊管理學系/碩士(2011年)

摘要

台灣汽車工業歷經半世紀的發展，已有長足的進步，尤其在台灣『汽車工業發展方案』施行後，台灣汽車工業技術能力顯著進步，競爭力不斷提升，目前已成為亞洲地區的零組件供應中心，成效卓著。
然而，台灣各家汽車廠在研發領域還是以改款設計為主，其關鍵技術仍舊需仰賴技術母廠。部分生產相關設備，也需透過日本相關企業，提供維修及零件支援。由於採購過程曠日廢時，技術支援也需日本派專人協助，為確保生產運作正常，須長時庫存相關維修備品，並定期聘請日本相關技術人員至現場檢測，人力物資所費不貲。
本研究旨在運用資料探勘(Data Mining)技術，探勘過往監測及檢修數據，期找出 Robot 噴塗設備異常之關聯規則，適時提出因應措施，以達到降低備品庫存及相關人力成本及之目的，並確保相關設備可正常運作，避免因設備異常造成的損失，協助企業追求利潤、提高企業競爭力。

關鍵字

資料探勘 ； 關聯規則 ； Robot 噴塗設備

並列摘要

The automobile industry in Taiwan has made significant progress in the past fifty years; especially after the implementation of Taiwan Automobile Development Policy, the techniques have been greatly improved with high quality, which has made Taiwan a crucial component supply center in Asia.
However, due to the heavy dependence on key technologies from the parent factory, most car manufacturers in Taiwan still remain in the field of modifying and trimming. Besides, they need the related companies in Japan to offer assistance of maintenance and component supplying. Because of that, plus time-consuming purchase, technique aid from specialists in Japan, and tracking of long-term inventory, factories here in Taiwan usually have to spend a considerable fortune every year to pay for human resources.
This research is to figure out how we can make more profits for businesses, cost down on human expenses and enforce business competitiveness through Data mining, detecting precedent data base and surveillance, finding out association rules of anomalistic operation of Robot spraying equipment, and proposing an appropriate solution in time.

並列關鍵字

Data mining ； Association rules ； Robot spraying equipment

參考文獻

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