應用資料探勘技術於維修知識推薦之研究-以飛機維修資料庫為例

A study of applying data mining techniques to maintenance knowledge recommendation -Aircraft maintenance database as example.

吳澤民(Tzer-Min Wu)

指導教授 ： 李維平

中原大學/商學院/資訊管理研究所/碩士(2002年)

https://doi.org/10.6840/cycu200200612

摘要

資訊科技的進步使得大部分的企業或組織皆已建立資訊系統來收集日常作業及管理等相關資料，當資訊系統收集了大量的資料在資料庫以後，企業更進一步思考能不能從這些儲存的資料中發現一些對企業有價值的資訊或知識，以便藉由這些知識的幫助來提升企業對外的競爭力。

維修領域是很強調專業技術及經驗累積的工作，近年來由於資訊科技的進步，已經可以將這些隱藏在工作人員身上的經驗及知識，藉由資訊系統的蒐集而保存在資料庫中，然而，如果無法將這些保存在資料庫中的資料轉化為對工作人員有用的知識，再藉由有效的資訊搜尋機制將其散播出去，這些保存在資料庫中的資料就如同隱藏的知識般，無法用它來進行知識的傳遞進而幫助經驗的交流。由於資料探勘技術在資料分析及知識擷取方面的研究上有非常豐富的成果，因此資料探勘技術在維修領域的應用與研究也逐漸受到重視。本研究希望將資料探勘技術應用於維修產業的維修知識擷取上，並嘗試以飛機維修資料庫為例，藉由資料探勘技術的輔助來建構飛機維修知識推薦系統，而能夠對飛機維修工作有所幫助進而達到維修經驗交流與知識傳承的目的。

我們先實驗傳統MBR方法得到初步的結果後，進一步分析實驗資料的特性而提出以類別為導向的MBR方法，稱之為CMBR(Class-Oriented MBR)，將以個別資料的特徵向量來測量與新資料間相似度的MBR方法，改以類別的關鍵字特徵來測量的CMBR方法，藉以改善分類的正確率及分類運算的執行效率。實驗結果顯示我們所提出的CMBR方法應用在飛機維修資料的分類上有較高的正確率。

最後我們以CMBR方法建立分類模型，藉以架構維修知識系統來輔助維修技術人員，使其能夠快速地找到故障現象對應的參考維修技術文件及可能的處理方式來完成維修工作。由於飛機線上維修的工作對於時間的要求非常嚴格，必須在最短的時間將飛機故障排除以便繼續飛行任務，而藉由本研究維修知識系統的輔助，將可縮短線上維修人員故障的判斷時間，使維修技術人員能夠快速地完成維修工作，並達成維修經驗傳承及知識傳遞的目標。

關鍵字

修護資料 ； 推薦系統 ； 飛機 ； 資料探勘 ； 知識擷取

並列摘要

Due to the development of information techniques in recent years. Lots of companies have setup information systems to collect the daily operation data and stored these data in the database. In order to enforce the competitive advantage for company. They want to retrieve some useful information and knowledge from data.

The maintenance engineering arises from professional field and experience accumulated. Since the development of information techniques, we use information systems to store the knowledge and experience of people in the database. If we can’t transfer these data to useful knowledge for people, then we can’t transfer knowledge to others from these data. The researches of data mining techniques have been developed very well in many fields. The application of data mining techniques in maintenance field being in paid much attention in these years. The purpose of this study is to apply data mining techniques to maintenance knowledge retrieval and to construct a maintenance knowledge recommendation system. This system can help maintenance engineer to finish their work more quickly.

This study applying traditional memory based reasoning technique (RMBR) to obtain a preliminary result and analysis the data character. Then we propose a class-oriented memory based reasoning technique (CMBR) to improve the accuracy and performance of classification. The experimental results of CMBR show a higher accuracy than traditional MBR (RMBR).

This study applying CMBR to construct a classified model and use this model to construct a maintenance knowledge recommendation system. This recommendation system can help maintenance engineer to find technical document and solution to complete his work. Because line maintenance must be completed in the shorten time. Helping by the maintenance knowledge recommendation system, then the maintenance engineer will do job well and quickly. In addition, he can acquire the experience from others.

並列關鍵字

data mining ； recommendation system ； maintenance data ； aircraft ； knowledge retrieval

參考文獻

[4] A. Famili and S. Letourneau, “Monitoring of Aircraft Operation using Statistics and Machine Learning”, 1999, National Research Council of Canada.

[7] Peter Turney and Michael Halasz, “Contextual Normalization Applied to Aircraft Gas Turbine Engine Diagnosis”, 1992, NRC #35028.

[12] Steven Salzberg, Book Review: "C4.5: Programs for Machine Learning" by J. Ross Quinlan, 1994, machine learning 1-6(1994).

[15] Mao, J., Jain, A.K., “Artificial Neural Networks for Feature Extraction and Multivariate Data Projection”, page 296-316 , in IEEE Trans.on Neural Networks, Vol.6, No.2, March 1995.

[16] S. K. PAL, S. MITRA: “Multilayer Perceptron, Fuzzy Sets and Classification.” page 683-697, 1992, IEEE Trans. on Neural Networks 3.