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논문 기본 정보

자료유형
학술저널
저자정보
저널정보
대한기계학회 Journal of Mechanical Science and Technology Journal of Mechanical Science and Technology Vol.19 No.5
발행연도
2005.5
수록면
1,072 - 1,079 (8page)

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초록· 키워드

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Conceptual design is the first step in the overall process of product design. Its intrinsic uncertainty, imprecision, and lack of information lead to the fact that current conceptual design activities in engineering have not been computerized and very few CAD systems are available to support conceptual design. In most of the current intelligent design systems, approach of principle synthesis, such as morphology matrix, bond graphic, or design catalogues, is usually adopted to deal with the concept generation, in which optional concepts are generally combined and enumerated through function analysis. However, as a large number of concepts are generated, it is difficult to evaluate and optimize these design candidates using regular algorithm. It is necessary to develop a new approach or a tool to solve the concept generation. Generally speaking, concept generation is a problem of concept synthesis. In substance, this process of developing design candidate is a combinatorial optimization process, viz., the process of concept generation can be regarded as a solution for a state-place composed of multi-concepts. In this paper, genetic algorithm is utilized as a feasible tool to solve the problem of combinatorial optimization in concept generation, in which the encoding method of morphology matrix based on function analysis is applied, and a sequence of optimal concepts are generated through the search and iterative process which is controlled by genetic operators, including selection, crossover, mutation, and reproduction in GA. Several crucial problems on GA are discussed in this paper, such as the calculation of fitness value and the criteria for heredity termination, which have a heavy effect on selection of better concepts. The feasibility and intellectualization of the proposed approach are demonstrated with an engineering case. In this work concept generation is implemented using GA, which can facilitate not only generating several better concepts, but also selecting the best concept. Thus optimal concepts can be conveniently developed and design efficiency can be greatly improved.

목차

Abstract

1. Introduction

2. Combination of Genetic Algorithm and Conceptual Design

3. Mathematical Description of Genetic Algorithm

4. Key Technologies of Genetic Algorithm-based Concept Generation

5. Conclusions

Acknowledgments

References

참고문헌 (11)

참고문헌 신청
Ermer, G., Rosenberg, R. et al., 1993, "Steps toward Integrating Function-based Models and Bond-graphs for Conceptual Design in Engineering," Automated Modeling for Design. ASME, Vol.47, No.11, pp.47~62. google schola Hoeltzel, D. A. and Chieng, W. H., 1990, "Knowledge-based Approaches for the Creative Synthesis of Mechanisms," Computer Aided Design, Vol. 22, No.1, pp.57~67. google schola Huang, H., Zhao, Z. and Guan, L., 2002, "Intelligent Conceptual Design Based on Genetic Algorithm," Journal of Computer-aided Design & Computer Graphics, Vol.14, No.5, pp.437~441. google schola Koza, J. R., 1992, Genetic Programming: on the Programming of Computers by means of Natural Selection, The MIT Press, Cambridge. pp.94~99. google schola Lim, O. K., Hong, K. S., Lee, H. S. et al.. 2004, "Initial Design Domain Reset Method for Genetic Algorithm with Parallel Processing,“ KSME International Journal, Vol.18, No.7, pp.1121~1130. google schola

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