GA-based synthesis approach for machining scheme selection and operation sequencing optimization for prismatic parts |
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Authors: | Guang-ru Hua Xiong-hui Zhou Xue-yu Ruan |
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Affiliation: | (1) National Die & Mold CAD Engineering Research Center, Shanghai Jiao Tong University, Shanghai, 200030, People’s Republic of China;(2) School of Mechanical Engineering, North China Electric Power University, 204 Qingnian Road, Baoding, Hebei Province, 071003, People’s Republic of China |
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Abstract: | To obtain global and near-global optimal process plans based on the combinations of different machining schemes selected from
each feature, a genetic algorithm-based synthesis approach for machining scheme selection and operation sequencing optimization
is proposed. The memberships derived from the fuzzy logic neural network (FL-NN), which contains the membership function of
each machining operation to batch size, are presented to determine the priorities of alternative machining operations for
each feature. After all alternative machining schemes for each feature are generated, their memberships are obtained by calculation.
The proposed approach contains the outer iteration and nested genetic algorithm (GA). In an outer iteration, one machining
scheme for each feature is selected by using the roulette wheel approach or highest membership approach in terms of its membership
first, and then the corresponding operation precedence constraints are generated automatically. These constraints, which can
be modified freely in different outer iterations, are then used in a constraints adjustment algorithm to ensure the feasibility
of process plan candidates generated in GA. After that, GA obtains an optimal process plan candidate. At last, the global
and near-global optimal process plans are obtained by comparing the optimal process plan candidates in the whole outer iteration.
The proposed approach is experimentally validated through a case study. |
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Keywords: | Machining scheme selection Operation sequencing optimization Genetic algorithm Computer aided process plan |
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