Application of Genetic Algorithm in the Study of Semantic Modeling Design of CNC Machine Tools

Abstract:

Because of the outstanding advantages of genetic algorithms in solving optimization problems of engineering design, in this paper, using genetic algorithm combined with Kansei Engineering as a optimal design method for product’s semantics modeling design, and using real-coded way to characterize shape characteristics of CNC machine tools, comprehensive accounted of user’s semantic needs and color Mido, then, established the fitness function, combined with the key components to complete the design. By case analysis shows that the method is feasible, and lays a foundation for intelligent design of CNC machine tools.

• Periodical: Advanced Materials Research (Volumes 472-475)
• Pages: 2235-2240
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.472-475.2235
• Online since: February 2012
• Authors: Tu Lan, Sheng Ju Tang, Bo Chen, De Ke Guo
• Keywords: CNC Machine Tool, Genetic Algorithm (GA), Kansei Engineering, Modeling Design

References

[1] Bo Chen, Shengju Tang, Tu Lan, Study on Form and Color of CNC Machine Tools Based on Kansei engineering[c], 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce(AIMSEC), 20011.8.

DOI: 10.1109/aimsec.2011.6010042

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