Intelligent Design Advisor: A Knowledge-Based Information System Approach for Product Development and Design

Quangang Yang and Reidsema Carl
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Quangang Yang: University of South Wales, Australia
Reidsema Carl: University of South Wales, Australia

International Journal of Enterprise Information Systems (IJEIS), 2006, vol. 2, issue 1, 1-16

Abstract: The rapid development of computing technology has facilitated its use in engineering design and manufacturing at an increasing rate. To deliver high quality, low cost products with reduced lead times, companies are focusing their efforts on leveraging this technology through the development of knowledge-based systems such as an IDA. An IDA, which can also be referred to as a design information system, is a part of the overall enterprise information system framework, and plays an important role in improving competitiveness in product development oriented companies. Not only must such a system utilize human expertise and address CE issues in decision making, it must also lead to the preservation and transfer of technical knowledge to minimize the knowledge loss from organizational moves such as personnel retirements and company relocation. The emphasis in CE is to consider downstream aspects of different phases in the product life cycle as early as possible in the design stage. These aspects include production process planning and realization, manufacturing and assembly resources, maintainability, costing and other factors. Both human expertise and downstream aspects predominantly consist of information that is descriptive. This paper discusses the structure and development of a knowledge-based design information system that can convert this descriptive information into forms that are suitable for embedding within decision-making algorithms. Information in such a system is sorted in terms of its nature into three groups: input data information, constraint information, and objective information, all having different representations. Information is also mapped to the relevant design objectives and ranked in importance to facilitate the trade-off analysis.

Date: 2006
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