Case retrieval(CR) is critically an important part of case-based design. However few studies attempt to research CR for customer-driven design and analyze the eect of other production factors besides similarity computation. This paper proposes a new CR method for customer-driven design,and requirement-weighting analysis. Fuzzy set theory are integrated into CR process to deal with the fuzzy and imprecision customer requirements. So the proposed method is called weighted fuzzy case retrieval(WFCR). Furthermore,similar case evaluation is added into CR process to demonstrate that the best case is selected not only on the basis of satisifaction for the given requriements,but also on the degree of preference over other cases according to multiple evaluation criteria. Meanwhile,WFCR system is developed and applied to power transformer design to validate its scientificity and practicality. Finally,the paper statistically validated the supriority of WFCR by comparing it with traditional fuzzy case retrieval methods(FCRs),and the comparison indicates that WFCR is more accurate than other FCRs.
A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.
Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional similarity based bio-inspiration transformation between biological domain and engineering domain is proposed. The biological function topology transfer and analog solution recomposition are also discussed in this paper.
This paper introduced a robust parameter coordination method to analyze parameter uncertainties so as to predict conflicts and coordinate parameters in multidisciplinary design. The proposed method is based on constraints network, which gives a formulated model to analyze the coupling effects between design variables and product specifications. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. To solve this constraint network model, a general consistent algorithm framework is designed and implemented with interval arithmetic and the genetic algorithm, which can deal with both algebraic and ordinary differential equations. With the help of this method, designers could infer the consistent solution space from the given specifications. A case study involving the design of a bogie dumping system demonstrates the usefulness of this approach.
An effective modeling method of domain level constraints in the constraint network for concurrent engineering (CE) was developed. The domain level constraints were analyzed and the framework of modeling of domain level constraints based on simulation and approximate technology was given. An intelligent response surface methodology (IRSM) was proposed, in which artificial intelligence technologies are introduced into the optimization process. The design of crank and connecting rod in the V6 engine as example was given to show the validity of the modeling method.
