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Genetic Algorithms for Manufacturing Process Planning

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Book cover Variants of Evolutionary Algorithms for Real-World Applications

Abstract

Process planning has been defined as the systematic determination of the machining methods (operations, machine, tool, fixture) by which a product is to be manufactured economically and competitively. A process plan describes the manufacturing processes for transforming a raw material to a completed part, within the available machining resources. This chapter presents the application of genetic algorithms (GAs) in computer aided process planning (CAPP), and the development of a CAPP system based on a GA. The key to successfully applying GAs to a real-world application such as process planning is to model the problem from an optimization perspective, and to design a special representation mechanism, operators, and constraints to introduce the domain knowledge into the algorithms. These steps are discussed in great detail to show how evolutionary algorithms such as GAs can be used to solve a difficult real-world problem along with their advantages.

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Author information

Authors and Affiliations

  1. Faculty of Department of Electronics & Mechanical, Wentworth Institute of Technology, Boston, MA, USA

    Guohua Ma

  2. The MathWorks, Natick, MA, USA

    Fu Zhang

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  1. Guohua Ma
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  2. Fu Zhang
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Editor information

Editors and Affiliations

  1. Faculty of ICT, Swinburne University of Technology, 3122, Melbourne, VIC, Australia

    Raymond Chiong

  2. Nature Inspired Computation and Applications Laboratory School of Computer Science and Technology, University of Science and Technology of China (USTC), 230027, Hefei, Anhui, China

    Thomas Weise

  3. School of Computer Science, University of Adelaide, 5005, Adelaide, SA, Australia

    Zbigniew Michalewicz

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© 2012 Springer-Verlag Berlin Heidelberg

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Ma, G., Zhang, F. (2012). Genetic Algorithms for Manufacturing Process Planning. In: Chiong, R., Weise, T., Michalewicz, Z. (eds) Variants of Evolutionary Algorithms for Real-World Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23424-8_7

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  • DOI: https://doi.org/10.1007/978-3-642-23424-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23423-1

  • Online ISBN: 978-3-642-23424-8

  • eBook Packages: EngineeringEngineering (R0)

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