Industrial Knowledge Management
A Micro-level Approach
Published on 6. December 2012
XIII, 569 pages
978-1-4471-0351-6 (ISBN)
Description
The book presents state of the art practices and research in the area of Knowledge Capture and Reuse in industry. This book demonstrates some of the successful applications of industrial knowledge management at the micro level. The Micro Knowledge Management (MicroKM) is about capture and reuse of knowledge at the operational, shopfloor and designer level. The readers will benefit from different frameworks, concepts and industrial case studies on knowledge capture and reuse. The book contains a number of invited papers from leading practitioners in the field and a small number of selected papers from active researchers. The book starts by providing the foundation for micro knowledge management through knowledge systematisation, analysing the nature of knowledge and by evaluating verification and validation technology for knowledge based system of frameworks for knowledge capture, reuse and development. A number integration are also provided. Web based framework for knowledge capture and delivery is becoming increasingly popular. Evolutionary computing is also used to automate design knowledge capture. The book demonstrates frameworks and techniques to capture knowledge from people, data and process and reuse the knowledge using an appropriate tool in the business. Therefore, the book bridges the gap between the theory and practice. The 'theory to practice' chapter discusses about virtual communities of practice, Web based approaches, case based reasoning and ontology driven systems for the knowledge management. Just-in-time knowledge delivery and support is becoming a very important tool for real-life applications.
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Book
10/2012
Springer
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10/2000
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Springer
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Content
1: Foundation.- Micro-Scale Knowledge Management: a necessary condition for getting corporate knowledge properly implemented.- Foundation of Knowledge Systematization: Role of Ontological Engineering.- A Conceptual Model for Capturing and Reusing Knowledge in Business-Oriented Domains.- Domain Knowledge in Engineering Design: Nature, Representation, and Use.- Selecting and Generating Concept Structures.- Evaluating Verification and Validation Methods in Knowledge Engineering.- 2: Frameworks.- Design Knowledge Acquisition and Re-Use Using Genetic Engineering-Based Genetic Algorithms.- A Web-Based Framework for Integrating Knowledge.- Re-Design Knowledge Analysis, Representation and Re-Use.- Project Memory in Design.- Micro Knowledge Management: A Job Design Framework.- Building the KDD Roadmap: A Methodology for Knowledge Discovery.- 3: Theory to Practice.- Supporting Virtual Communities of Practice.- Managing Micro- and Macro-level Design Process Knowledge across Emergent Internet Information System Families.- The Development of Case-Based Reasoning for Design - Techniques and Issues.- An Internet-Based Approach to the Capture and Reuse of Knowledge in Design.- Ontology-Driven Knowledge Management: Philosophical, Modelling and Organizational Issues.- 4: Tools.- Micro-Modelling of Business Processes for Just-in-Time Knowledge Delivery.- Just-in-Time Knowledge Support.- STEP PC: A Generic Tool for Design Knowledge Capture and Reuse.- WebGrid: Knowledge Elicitation and Modelling on the World Wide Web.- Mapping for Reuse in Knowledge-Based Systems.- Mining Very Large Databases to support Knowledge Exploration.- 5: Industrial Case Study.- Knowledge Management for the Strategic Design and Manufacture of Polymer Composite Products.- Cutting Tool Design Knowledge Capture.- AnOrganic Architecture for Distributed Knowledge Management.- Life-cycle knowledge management in the design of large made-to-order (MTO) products.- A Case-Study on Manufacturing Knowledge Capture: XPat to CommonKADS.- CommonKADS and Use Cases for Industrial Requirements Gathering.- 6: The Future.- Model Framework for Sharing of Engineering Practice Knowledge through ubiquitous networks of Learning Communities.- Managing Engineering Knowledge Federations.- Languages for Knowledge Capture and their Use in Creation of Smart Models.- Ontologies for Knowledge Management.- 7: Resource Guide.
