Optimization of geometry quality model for wire and arc additive manufacture based on adaptive multi-objective grey wolf
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METHODOLOGIES AND APPLICATION
Optimization of geometry quality model for wire and arc additive manufacture based on adaptive multi-objective grey wolf algorithm Yun-tao Zhao1,3
•
Wei-gang Li1 • Ao Liu2
Springer-Verlag GmbH Germany, part of Springer Nature 2020
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. Keywords Wire and arc additive manufacture Intelligent algorithm Multi-objective grey wolf algorithm TOPSIS
1 Introduction Wire and arc additive manufacture (WAAM) is a complex physical and chemical process; it has attracted much attention for its unique advantages of high efficiency and low cost in manufacturing large-scale metal parts (Geng et al. 2017). The selection of process parameters in WAAM has a significant impact on the geometry quality of weld bead and the dimensional accuracy of parts (Kannan and Murugan 2006). The dimensional accuracy of parts is determined by the geometric structure of weld bead in single layer. The uniformity and stability of geometric
Communicated by V. Loia. & Yun-tao Zhao [email protected] 1
Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education, Wuhan 430081, China
2
School of Management, Wuhan University of Science and Technology, Wuhan 430081, China
3
School of Information Science and Engineering, Wuhan University of Science and Technology, No. 947, Heping Road, Qingshan District, Wuhan 430081, Hubei, China
structure determine the final-dimensional accuracy of parts. Therefore, the selection of the optimal process parameters to obtain the desired accuracy of parts is of great significance for the automated production of WAAM. The geometric structure of weld bead in WAAM is influenced by various process parameters (such as welding voltage, wire feed rate, welding speed, nozzle-to-plate distance, interpass temperature, wire feed angle, and gas flow) (Rios et al. 2018; Shen et al. 2017; Xiong et al. 2018). These parameters interact with each other, so that it is difficult for skilled operators to choose the appropriate combination of parameters to achieve the best geometry quality of weld
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