汽車電子產業結合電子資訊優勢於傳統汽車產品零組件內，使得汽車更具有智慧性資訊功能，並同時延伸出電子資訊產業的另一應用領域商機。但在跨產業的產品整合中，個別產品零組件問題，可能會影響到整個產品的品質和效用，進而攸關到顧客使用汽車電子的安全性和應用性。產品零組件的現有問題會發生在維修作業，而其潛在問題則會在保養作業中發現，這些問題資料是具有模糊性質，傳統上診斷問題的方式是憑維修人員的經驗或是碰巧發覺的可能性，沒有一個系統化的機制，因此可能造成誤判或時間的浪費，故如何以系統化方式整合產品問題資料，進而建構具有處理模糊性質資料能力的維修保養知識庫，就成為汽車和電子產業結合是否有優勢和商機的關鍵。 本文結合模糊歸屬函數和物件導向方法，來建構具有模糊處理能力之物件導向知識庫，能將診斷出之現有問題原因所在與潛在問題視為知識物件儲存其中，將來遇到類似問題就能快速診斷出原因，並針對診斷出的潛在問題事先預防，將其轉變成現有問題，進一步減少其產生的機率。 本文的貢獻：1.應用AHP方法建構一套診斷維修問題原因所在的系統化決策模式, 2.提出模糊物件導向結構化語言來處理產品維修保養問題，其中包括發展出模糊運算子結合關聯查詢的演算法。3. 透過導入介面物件的概念，和運用模糊歸屬函數、fuzzy object-oriented SQL，來提出具有模糊決策能力，進而預防產品潛在問題發生的的知識庫。

Incorporating the advantages of computer electronics into conventional automobile products in the automobile electronics industry, facilitates intelligent functions for automobiles and provides another field of commercial opportunity for the computer electronics industry. Regarding cross-industrial product integration, problems in specific parts may affect the quality and performance of the entire product and affect the safety and applicability of automobile electronics. Existing problems in product components occur during repair, and potential problems will occur during maintenance. The data gathered from these problems have fuzzy characteristics. Traditional problem diagnosis has relied on the experience of maintainers or coincidental findings. The absence of a systematic mechanism has increased the likelihood that maintainers might produce erroneous judgments or waste time. Therefore, systematically compiling product-problem data and constructing a repair and maintenance database, which has the ability to manage fuzzy data for integrating the automobile and computer electronics industry, is crucial. This paper combines the fuzzy membership function and the object-oriented method to construct a knowledge base to manage fuzzy data and to explore the problems and potential problems diagnosed as knowledge objects, which are stored in it. This approach would enable diagnosing similar problems in advance and transform them into existing problems to reduce their probability of occurring. We first proposes a systematic mechanism to address the product repair and maintenance problem and to prevent the occurrence of potential problems. This mechanism reduces repair frequency and maintenance cost. We subsequently propose a knowledge base of customer feedback and fuzzy decision making as the foundation of customer active point.