智慧型問題診斷系統之構建—以園區通訊廠商品質系統為例

Abstract

以往維修人員在面對診斷問題時，僅能依靠經驗累積的方式，來找出故障原因，但由於員工的流動頻繁，使得企業面臨著資深員工培養不易的情況。近年來由於專家系統的發展已有相當的成果，有不少的研究利用專家系統來輔助人員進行問題診斷，也都有不錯的成效。但是在專家系統的建構過程中，系統建構者卻往往面臨著知識擷取困難及系統維修不易等問題。本研究希望運用類神經網路，發展一套通用型之問題診斷機制。首先對於系統做一個分析與整理，將系統中的問題特徵，利用量化的技巧加以量化。接著根據問題的特徵與相對應之問題發生原因以及可能解決方法，試著建立類神經網路模式。本研究所建立的模式，可以在系統發生特定問題時，能夠找出問題的可能發生原因以及解決的辦法，提升製造業系統之績效，節省不必要的浪費。 本研究以園區通信廠商品質系統為例，發展一套品質系統問題診斷機制，在本案例中，對於製程管制部分以及研發管制部分的診斷正確率皆達到90%左右。研究結果顯示，本研究所提方法具有相當的可行性。

In the past, when mechanics diagnose the breakdown situations, they only can rely on accumulated experiences and find out the causes. Recently, employee come and go frequently. Enterprises faces the problem of keeping experienced employee. In recent years, due to the development of expert system is quite fruited; in many researches, mechanics diagnose breakdown situations with the assistance of expert system and the outcome is pleasant . However, during the process of building expert system , system builders usually face the problems such as knowledge gathering and system repair. Our institute hopes to apply neural network to build a general model of diagnostic mechanism. First of all, we analyze and gather the system and then quantify the characteristics of the system. Finally, we try to build neural network model via the characteristics of the problems, causes of relative problems and possible resolvable ways. When specific problems occurs, our model can find out possible reasons and resolvable ways , improve the effect of manufacture system and save unnecessary waste. Our institute uses the quality systems of communication manufactures in science zone as sample and tries to build a quality system diagnostic mechanism. In our case, the diagnostic of making process control and invention control reaches 90 %.Our research reveals that the method we mentioned is quite feasible. 英文摘要…………………………………………………………ii 誌謝………………………………………………………………iii 目錄………………………………………………………………iv 圖目錄……………………………………………………………vi 表目錄……………………………………………………………vii 第一章 緒論………………………………………………………1 1.1 研究背景與動機………………………………………1 1.2 研究目的………………………………………………2 1.3 研究範圍與限制………………………………………2 1.4 研究架構與步驟………………………………………3 第二章 文獻探討…………………………………………………5 2.1 類神經網路……………………………………………5 2.1.1 倒傳遞網路理論………………………………………7 2.1.2 學習向量量化網路…….……………………………9 2.1.3 機率神經網路……………....………………………10 2.1.4 放射基準機能網路………….………………………11 2.2 類神經網路於問題診斷與分類之應用………………11 第三章 問題診斷系統構建流程…………………………………16 第四章 實例說明…………………………………………………21 4.1 個案說明………………………………………………21 4.2 診斷系統構建…………………………………………22 4.3 比較……………………………………………………37 第五章 結論與建議………………………………………………39 參考文獻……………………………………………………………41 附錄…………………………………………………………………44