Knowledge-Intensive Collaborative Decision Support for Design Process, Part 1: A Hybrid Decision Model and Multi-Agent Framework
XuanFang Zha, Ram D. Sriram, M Fernandez, F Mistree
Engineering design is essentially a collaborative decision-making process that requires rigorous evaluation, comparison and selection of design alternatives and optimization from a global perspective. Increasing design knowledge and supporting designers to make intelligent and correct decisions can result in higher quality designs. In this paper we present a hybrid decision support model and framework, focused on facilitating the integration of objective and subjective aspects of design, which can be extensively applied for engineering systems. The proposed system will facilitate the seamless/smooth integration of the stakeholder involved in collaborative product development and improve the likelihood of optimal product performance. The work focuses on the provision of methodologies/algorithms and a framework for knowledge-based intelligent design decision-making for improved product development and realization of business strategies. The reported hybrid decision model, which integrates the compromise Decision Support Problem (cDSP) and the fuzzy synthetic model (FSD), can quantitatively incorporate qualitative design knowledge and preferences for multiple, conflicting attributes stored in a knowledge repository so that a better understanding of the consequences of design decisions can be achieved from an overall perspective. The developed model and framework are generic and flexible enough to be used in a variety of design decision problems. The framework is illustrated with an application in concept evaluation and selection in product family design for mass customization.
, Sriram, R.
, Fernandez, M.
and Mistree, F.
Knowledge-Intensive Collaborative Decision Support for Design Process, Part 1: A Hybrid Decision Model and Multi-Agent Framework, Journal of Mechanical Design, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822294
(Accessed December 8, 2023)