A framework for management of Knowledge-Based Engineering applications as software services: Enabling personalization and codification

Literature on Knowledge-Based Engineering (KBE) has identified challenges concerning the personalization and codification of knowledge for new product development, such as maintaining the quality, accessibility and traceability of knowledge for inspection, review and re-use, as well as managing the life-cycle of KBE applications and the knowledge contained within these applications. This paper reports on the development of a framework that realizes the management of Knowledge-Based Engineering (KBE) applications as software services, and in doing so supports the codification and personalization of knowledge that is used in performing knowledge-intensive product development tasks. The developed framework supports the elicitation and structuring of design and manufacturing knowledge, provides the capacity to run KBE applications as remote software services, and facilitates the distribution and lifecycle management of KBE applications and the underlying knowledge. A 'learning by doing' approach is supported where knowledge can both be personalized and codified as design progresses and new insights are gained. The framework has been successfully applied in an industrial use case that considers the conceptual design of composite aircraft wing covers.

[1]  Jin Wu,et al.  Quality-Assisted Multi-Objective Multidisciplinary Genetic Algorithms , 2002 .

[2]  T Haftka Raphael,et al.  Multidisciplinary aerospace design optimization: survey of recent developments , 1996 .

[3]  M. J. L. van Tooren,et al.  Enabling distributed multi-disciplinary design of complex products: a knowledge based engineering approach , 2007 .

[4]  Morten T. Hansen,et al.  What's your strategy for managing knowledge? , 1999, Harvard business review.

[5]  Zafer Gürdal,et al.  Multi-step blended stacking sequence design of panel assemblies with buckling constraints , 2009 .

[6]  Pablo Bermell-Garcia,et al.  Practitioner requirements for integrated Knowledge-Based Engineering in Product Lifecycle Management , 2008 .

[7]  Christos Kassapoglou,et al.  Stacking Sequence Blending of Multiple Composite Laminates Using Genetic Algorithms , 2002 .

[8]  M. J. L. van Tooren,et al.  Integration of friction stir welding into a multi-disciplinary aerospace design framework , 2006, The Aeronautical Journal (1968).

[9]  M. Lynne Markus,et al.  Toward A Theory of Knowledge Reuse : Types of Knowledge Reuse Situations and Factors in Reuse Success , 2022 .

[10]  Shu-Hsien Liao,et al.  Expert system methodologies and applications - a decade review from 1995 to 2004 , 2005, Expert Syst. Appl..

[11]  John Davies,et al.  Knowledge capture and utilization in virtual communities , 2001, K-CAP '01.

[12]  Steve Culley,et al.  Knowledge management in engineering design: personalization and codification , 2004 .

[13]  Chris A McMahon,et al.  Information management for through life product support: the curation of digital engineering data , 2005 .

[14]  Dimitris Kiritsis,et al.  An ontology-based approach for Product Lifecycle Management , 2010, Comput. Ind..

[15]  Pablo Bermell-Garcia.  A metamodel to annotate knowledge based engineering codes as enterprise knowledge resources , 2007 .

[16]  Pablo Bermell-Garcia,et al.  A critical review of Knowledge-Based Engineering: An identification of research challenges , 2012, Adv. Eng. Informatics.

[17]  I. Nonaka.  A Dynamic Theory of Organizational Knowledge Creation , 1994 .

[18]  Carys Siemieniuch,et al.  Organizational aspects of knowledge lifecycle management in manufacturing , 1999, Int. J. Hum. Comput. Stud..

[19]  Derek H. Sleeman,et al.  Constraint capture and maintenance in engineering design , 2008, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[20]  Russell M. Cummings,et al.  Airplane design: Past, present, and future , 2002 .

[21]  Jan L. Top,et al.  Engineering ontologies , 1997, Int. J. Hum. Comput. Stud..