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

• Published in: Computer aided design Vol. 45; no. 2; pp. 204 - 228
• Main Authors: Chandrasegaran, Senthil K., Ramani, Karthik, Sriram, Ram D., Horváth, Imré, Bernard, Alain, Harik, Ramy F., Gao, Wei
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2013
• Subjects: Collaborative engineering; Computational tools; Computer simulation; Decisions; Design engineering; Design rationale; Evolution; Knowledge capture; Knowledge management; Knowledge representation; Mathematical models; Multidisciplinary modeling; Ontology; Product design; Simulation; Systems engineering; Virtual reality; Design rationale; Ontology; Simulation; Knowledge capture; Systems engineering; Knowledge representation; Computational tools; Multidisciplinary modeling; Virtual reality; Knowledge management; Product design; Collaborative engineering
• ISSN: 0010-4485; 1879-2685
• DOI: 10.1016/j.cad.2012.08.006

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. [Display omitted] ► Definition and classification of knowledge and knowledge representation. ► Review of the evolution of the role of knowledge representation in product design. ► Review of computational tools for knowledge representation in research and industry. ► Technology convergence and their potential effects on future trends in product development.