The evolution, challenges, and future of knowledge representation in product design systems

  • Authors:

  • Senthil K. Chandrasegaran;Karthik Ramani;Ram D. Sriram;Imré HorváTh;Alain Bernard;Ramy F. Harik;Wei Gao

  • Affiliations:

  • School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA;School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA and School of Electrical Engineering (by courtesy), Purdue University, West Lafayette, IN, 47907, USA;National Institute of Standards and Technology, Gaithersburg, MD 20899, USA;Faculty of Industrial Design Engineering, Delft University of Technology, 2628CE Delft, The Netherlands;Ecole Centrale de Nantes, 44321 Nantes Cedex 03, France;Department of Industrial and Mechanical Engineering, Lebanese American University, Byblos, Lebanon;School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA

  • Venue:
  • Computer-Aided Design
  • Year:
  • 2013

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Abstract

Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.