Fuzzy decision-making approach of hobbing tool and cutting parameters

Abstract

Machining performance, such as carbon emission, machining time, and quality, can be improved by selecting appropriate tools and cutting parameters for gear hobbing. However, the importance machining performance is usually difficult for users to quantify. To resolve the decision-making problem of hobbing tools and cutting parameters in fuzzy evaluation, a multi-objective fuzzy decision-making approach for hobbing parameters is proposed. It uses spectral clustering, the multi-objective weighted mean of vectors (MOINFO) algorithm and the fuzzy technique for ordering preference by similarity to the ideal solution (TOPSIS) algorithm. First, spectral clustering is used to confirm the initial range of the hobbing parameters based on past machining cases. MOINFO is then applied to search for nondominated hobbing parameters based on the optimization model, taking the carbon emission, cutting time, and quality as the objectives. Finally, the nondominated hobbing parameters are sorted by fuzzy TOPSIS according to a user evaluation, and the hobbing parameter ranking is used to guide hob selection and machining. Decision-making experiments on the hobbing parameters are performed with actual hobbing. The comprehensive evaluation index CEI result for the proposed approach is 0.19. Compared with other methods, the proposed approach exhibits certain advantages. These results demonstrate that the multi-objective decision-making problem of hobbing parameters under fuzzy evaluation can be solved using the proposed approach.