Data-driven Decision-making Approach of Laser Cladding Parameters for Low Carbon

Abstract The machining performance, such as carbon emission, dilution ratio rate, and powder utilization can be improved by selecting appropriate process parameters in laser cladding. However, the importance evaluation of performance users is often fuzzy. How to make a reasonable decision about cladding under this condition? To resolve problem, multi-objective fuzzy decision-making approach proposed using support vector regression (SVR), dragonfly algorithm (MODA), TOPSIS. Firstly, SVR used build correlation model among parameters. Secondly, MODA applied search non-dominated (non-dominated solution) based on model. Finally, are sorted TOPSIS according user’s evaluation, parameter ranking first that best meet requirements users, feasibility effectiveness verified via experiments. low-carbon problem well solved approach.