Multi-response optimization of laser cladding for TiC particle reinforced Fe matrix composite based on Taguchi method and grey relational analysis. (September 2022) - Deng, Dewei; Li, Tianshu; Huang, Zhiye; Jiang, Hao; Yang, Shuhua; Zhang, Yong
Highlights: ANOVA was used to investigate the effects of process parameters on laser cladding. Six responses of TiC/Fe composite cladding layer were converted into GRG . GRG was improved by optimizing laser cladding process parameters. The shielding gas flow rate has a significant effect on the cladding layer. Abstract: The cladding layers of TiC particle reinforced Fe matrix composite was fabricated by pre-placed powder laser cladding. The clad height, width, dilution rate, hardness, content of unmelted TiC particles and porosity were selected as response. The effects of process parameters, especially the shielding gas flow rate which has received less attention so far, on the response were investigated by analysis of variance (ANOVA) based on L25 (5 3 ) Taguchi orthogonal experimental design. It was found that shielding gas flow rate had a significant effect on clad height, hardness and content of unmelted TiC particles. Combining with grey relational analysis (GRA) optimized the objectives of minimum height, maximum width, suitable dilution rate, maximum hardness, minimum content of unmelted TiC particles and minimum porosity by converting the six responses into grey relational grade ( GRG ). The optimal level of laser power, scanning speed and shielding gas flow rate is 1800 W, 6 mm/s and 6 L/min, respectively. The results of the validation experiments show that there is a minor error in the grey relational grade compared to the predicted value, and the grey relational grade improved by 0.229 after parameter optimization. The combination of Taguchi method and grey relational analysis (TGRA) can give a preferable optimization for multi-parameter laser cladding processes.