Optimization of cutting parameters in multi-pass turning using artificial bee colony-based approach

Selection of cutting parameters in machining operations is an essential task to reduce cost of the products and increase quality. This paper presents an optimization approach based on artificial bee colony algorithm for optimal selection of cutting parameters in multi-pass turning operations. The objective is to find the optimized cutting parameters in the turning operations. A comparison of evolutionary-based optimization techniques to solve multi-pass turning optimization problems is presented. The results of the proposed approach for the case studies are compared with previously published results by using other optimization techniques in the literature.

► A new hybrid optimization method (HABC) based on artificial bee colony algorithms is developed.
► The HABC is applied to the manufacturing optimization problems.
► A comparison of state-of-the-art optimization techniques to solve multi-pass turning optimization problems is presented.
► The HABC gives a robust way for obtaining optimal results in turning operations.