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Optimization of geometry quality model for wire and arc additive manufacture based on adaptive multi-objective grey wolf algorithm

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Abstract

In order to obtain good geometry quality in the wire and arc additive manufacture, it is important to select the appropriate process parameters. Firstly, based on the 4-factor and 5-level experiments, the multi-objective mathematical model of process parameters and geometry quality is established by response surface methodology. Secondly, an adaptive grey wolf algorithm for solving multi-objective problems is proposed. The algorithm introduces external Archive, adaptive hunting mechanism, and fusion polynomial mutation mechanism to improve the search ability of the grey wolf algorithm. Experiments show that the Pareto set obtained by the adaptive multi-objective grey wolf algorithm is more diverse and convergent than the other five well-known algorithms. Meanwhile, in order to obtain the desired geometry quality, the TOPSIS algorithm is used to analyze the Pareto set obtained to get the optimal process parameters.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve this paper. This work is supported by the National Natural Science Foundation of China [Grant Number 51774219] and the Science and Technology Research Program of Hubei Ministry of Education [Grant Number MADT201706].

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Correspondence to Yun-tao Zhao.

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Zhao, Yt., Li, Wg. & Liu, A. Optimization of geometry quality model for wire and arc additive manufacture based on adaptive multi-objective grey wolf algorithm. Soft Comput 24, 17401–17416 (2020). https://doi.org/10.1007/s00500-020-05027-y

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