An Uncertainty Evolution Model for Product Conceptual Design Based on Fuzzy Reasoning Petri Nets

Abstract

Because of the fuzzy and uncertain information in the conceptual design stage, it is difficult for multidisciplinary design to converge to consistency. In the decision-making process of product conceptual design, it is helpful to obtain a more reliable and robust conceptual design solution with the consideration of uncertainty and fuzzy knowledge. The essence of the conceptual design process is the thinking process of the design product, and quantitative analysis methods have been proposed to research the design uncertainty. In order to capture the quantitative relationship between design uncertainty and design elements, and to clarify the perception-cognitive behavior in uncertainty, in this paper, a product conceptual uncertainty evolution model based on fuzzy reasoning Petri nets is proposed. The uncertainty reasoning with diverse structures is embedded in fuzzy production rules. The rules are imported from the uncertain simulation data mined by rough sets, and the fuzzy reasoning algorithm is implemented through multi-standard rules to simulate the uncertainty of product conceptual design environment and monitor the uncertainty of conceptual design process. The validity of the model is verified by case analysis, and it may provide decision support for the product conceptual design process.