The effective use of computer based tools to support decision making in manufacturing industry is critical to business success. One of the most critical areas is during product design and especially in design for manufacture. This research will help in understanding of how manufacturing knowledge can be effectively maintained for an existing knowledge base. The work will use modern product lifecycle management tools in combination with a knowledge based environment in order to explore the effectiveness of the methods produced. This work is a part of the SAMULET (Strategic Affordable Manufacturing in the UK through Leading Environmental Technologies) research program and was done in association with an aerospace manufacturing company. The main focus of this research is to define a novel method for maintaining the machining knowledge associated with manufacturing of Xtra Wide Body (XWB) High Pressure (HP) turbine blade. The four main elements explained in this thesis are, a) the literature review done on knowledge management and knowledge maintenance, b) industrial investigation done on a manufacturing facility, c) detailed explanation of a novel manufacturing knowledge maintenance method d) four iterative case studies used for the evaluation and iterative improvement of the method. The research concludes that the aspect of knowledge maintenance is important. It is imperative to set out a formalised and mandated knowledge maintenance process in an organisation to keep the knowledge up-to-date and relevant. It has been shown that a novel task based knowledge maintenance method comprising a Knowledge Maintenance Process (KMP) and a Knowledge Maintenance Template (KMT) provides an effective route to knowledge maintenance. Three maintenance tasks, check relevancy, knowledge filtering, and integrity checking have been considered in detail for successful knowledge maintenance. Four iterative case studies have been conducted for the experimental evaluation of the maintenance method. As the result of these evaluations a novel method for maintaining the machining knowledge of XWB HP turbine blade was defined.

知識資源是組織競爭優勢的重要來源，而專業服務業則是知識經濟中知識型企業的類型之一，其知識資源的運作是值得深入探討的問題。本研究以組織能力的角度觀察知識整合與維持，探討專業服務業知識整合與組織能力的關係，分析其知識整合與知識維持的模式，以及影響知識整合與知識維持模式之因素。 研究採用個案研究方法，透過資料文獻的收集整理，以及四家個案公司的深度訪談分析，主要得到以下的研究發現。 一、專業服務業的知識整合模式 知識資源整合模式由「整合層次」、「整合機制」、「組織文化」三者觀察，共有三種類型。 1.「有機多元團隊模式」採跨部門整合，組織文化偏有機式。對話溝通與共同語言使用頻繁，專業個人機制常與例規的搭配。跨部門層次知識整合機制非常多元，共同會議具有重要地位，團隊由T型人員擔任整合者角色。 2.「機械流程模式」採跨部門整合，組織文化偏機械式。部門間少有對話溝通，有清楚的工作規則與作業準則。跨部門層次知識整合機制以流程的整合機制為主導。 3.「專業個人主導模式」採部門內整合，具有有機式的組織文化。個人層次的專業個人判斷是完成組織任務的關鍵，專業共同語言體系複雜，對話溝通主要是資訊交流，非任務決策的討論。 二、組織能力任務知識特性與知識整合模式的關係 專業服務業中，組織能力的任務知識特性不同，知識整合模式亦不同。當任務知識複雜性高、內隱性高時，採用「有機多元團隊模式」。當任務知識複雜性高、內隱性低時，採用「機械流程模式」。當任務知識複雜性低、內隱性高時，則採用「專業個人主導模式」。 三、專業服務業的知識維持模式 組織能力的知識資源維持模式可以由「減少依賴策略」、「減少不確定策略」二者觀察，共有三種類型。 1.「知識擴散模式」透過工作過程中的知識交流，以及教育訓練或師徒制的傳承制度，使得知識能擴散開來。不同類型專家各自參與部分任務，透過團隊默契的建立與組織認同，使得知識能夠長期累積與彈性運用。 2.「知識外化模式」將完成任務的主要知識不斷地有系統地紀錄下來，使組織能降低因員工離去而帶走知識的風險。 3.「知識穩定模式」則是組織提供良好的工作環境以及有吸引力的報酬制度，使得關鍵員工願意繼續留在組織中。組織並會致力於專業知識分享之機制，使其減少對少數關鍵專業員工的依賴程度。 四、組織能力任務知識特性與知識維持模式的關係 專業服務業中，組織能力的任務知識特性不同，組織能力的知識維持模式亦不同。當任務知識複雜性高、內隱性高時，採用「知識擴散模式」。當任務知識複雜性高、內隱性低時，採用「知識外化模式」。當任務知識複雜性低、內隱性高時，則是採用「知識穩定模式」。

The present work deals with Description Logics (DLs), a class of knowledge representation formalisms used to represent and reason about classes of individuals and relations between such classes in a formally well-defined way. We provide novel results in three main directions. (1) Tractable reasoning revisited: in the 1990s, DL research has largely answered the question for practically relevant yet tractable DL formalisms in the negative. Due to novel application domains, especially the Life Sciences, and a surprising tractability result by Baader, we have re-visited this question, this time looking in a new direction: general terminologies (TBoxes) and extensions thereof defined over the DL EL and extensions thereof. As main positive result, we devise EL++(D)-CBoxes as a tractable DL formalism with optimal expressivity in the sense that every additional standard DL constructor, every extension of the TBox formalism, or every more powerful concrete domain, makes reasoning intractable. (2) Non-standard inferences for knowledge maintenance: non-standard inferences, such as matching, can support domain experts in maintaining DL knowledge bases in a structured and well-defined way. In order to extend their availability and promote their use, the present work extends the state of the art of non-standard inferences both w.r.t. theory and implementation. Our main results are implementations and performance evaluations of known matching algorithms for the DLs ALE and ALN, optimal non-deterministic polynomial time algorithms for matching under acyclic side conditions in ALN and sublanguages, and optimal algorithms for matching w.r.t. cyclic (and hybrid) EL-TBoxes. (3) Non-standard inferences over general concept inclusion (GCI) axioms: the utility of GCIs in modern DL knowledge bases and the relevance of non-standard inferences to knowledge maintenance naturally motivate the question for tractable DL formalism in which both can be provided. As main result, we propose hybrid EL-TBoxes as a solution to this hitherto open question.

The present work deals with Description Logics (DLs), a class of knowledge representation formalisms used to represent and reason about classes of individuals and relations between such classes in a formally well-defined way. We provide novel results in three main directions. (1) Tractable reasoning revisited: in the 1990s, DL research has largely answered the question for practically relevant yet tractable DL formalisms in the negative. Due to novel application domains, especially the Life Sciences, and a surprising tractability result by Baader, we have re-visited this question, this time looking in a new direction: general terminologies (TBoxes) and extensions thereof defined over the DL EL and extensions thereof. As main positive result, we devise EL++(D)-CBoxes as a tractable DL formalism with optimal expressivity in the sense that every additional standard DL constructor, every extension of the TBox formalism, or every more powerful concrete domain, makes reasoning intractable. (2) Non-standard inferences for knowledge maintenance: non-standard inferences, such as matching, can support domain experts in maintaining DL knowledge bases in a structured and well-defined way. In order to extend their availability and promote their use, the present work extends the state of the art of non-standard inferences both w.r.t. theory and implementation. Our main results are implementations and performance evaluations of known matching algorithms for the DLs ALE and ALN, optimal non-deterministic polynomial time algorithms for matching under acyclic side conditions in ALN and sublanguages, and optimal algorithms for matching w.r.t. cyclic (and hybrid) EL-TBoxes. (3) Non-standard inferences over general concept inclusion (GCI) axioms: the utility of GCIs in modern DL knowledge bases and the relevance of non-standard inferences to knowledge maintenance naturally motivate the question for tractable DL formalism in which both can be provided. As main result, we propose hybrid EL-TBoxes as a solution to this hitherto open question.