現代人的生活與網路息息相關，而在一般家庭中與網路介接的方式大部分為寬頻網路，當生活上大小事均依靠網路解決，與網路接觸的時間越長，對於寬頻網路的品質要求則越高，但是一般網路供應商之寬頻接取設備可能會因為溫度、濕度、電壓等環境因素的變化以及設備本身零件的老化，產生設備的異常行為導致用戶上網時受到影響，如網路速度緩慢、上網瞬斷等障礙，通常發生這樣的狀況都是由客戶自己申告障礙，網管人員及客網人員無法在客戶申告前察覺客戶已經有網路不良的狀況。
本論文主要藉由收集網管人員及客網人員平日設備及線路維護的經驗累積，歸納出一般障礙的現象規則，並依此建立一知識庫。再藉由分析超高速數位用戶迴路之用戶連線信號狀態，是否有異常網路瞬斷，將疑似障礙設備影響之用戶過濾出來，並透過代理人使用知識庫來自動分析可能的障礙原因，提供客網人員及網管人員建議處理方式，以減少障礙判斷時間，最終的目標是希望客戶障礙申告之前就可將障礙處理完畢。
本研究經由實作及實驗分析後，卻可有效將障礙過濾出來，並找出排除障礙的方法，在用戶向電信公司申告障礙之前，即可將大部分之障礙處理完畢，大量地減少用戶端及客網人員及網管人員的困擾。

Modern life is so closely related to the Internet, with households connected to the Internet via broadband network. Nowadays, almost everything can be done through the Internet. As our reliance on the Internet deepened, the expectations for the quality of the broadband network also deepened. However, broadband network access equipment of Internet service providers may be unstable due to temperature changes, humidity variations, electricity stability, and aging, and cause breakdown, interruptions, or slow connections. Often, these failures are acknowledged only after customers file complaints and Internet service providers are unable to detect them in advanced or in real-time.
This thesis collects the experiences of network management engineers in daily maintenance of equipment and network cables and call center in dealing with the complaints from customers for establishing the rules of general failure phenomena in order to build a knowledgebase of common signs of errors. To determine if there is any abnormality in the users’ connection, this study uses agents to scan the very high speed Digital Subscriber Lines to detect short interruptions or slowdown in connection speed. If there is abnormality found, the agents use the knowledgebase to infer what might be the causes. The result of the inference also provides network management engineers and the call center recommended solutions to reduce error identification time and, hopefully, to eliminate the abnormalities before customers realize them and files for customer supports.
The mechanism implemented in this research proves, through experiments and results analysis, effective both in isolating the errors and in delivering recommended solutions to the problem. Most issues can be eradicated before customers are aware of the errors. The mechanism is efficient in reducing unnecessary hassles for the customers, the network management engineers, and the call center.

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