Metamodel-based multi-objective optimization of a turning process by using finite element simulation. Issue 7 (2nd July 2020)

• Record Type: Journal Article
• Authors: Amouzgar, Kaveh; Bandaru, Sunith; Andersson, Tobias; Ng, Amos H. C.
• Is Part Of: Engineering optimization. Volume 52:Issue 7(2020)
• Page Start: 1261
• Page End: 1278
• Publication Date: 2020-07-02
• Subjects: Metamodelling -- surrogate models -- machining -- turning -- multi-objective optimization; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2019.1639050
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This study investigates the advantages and potentials of the metamodel-based multi-objective optimization (MOO) of a turning operation through the application of finite element simulations and evolutionary algorithms to a metal cutting process. The objectives are minimizing the interface temperature and tool wear depth obtained from FE simulations using DEFORM-2D software, and maximizing the material removal rate. Tool geometry and process parameters are considered as the input variables. Seven metamodelling methods are employed and evaluated, based on accuracy and suitability. Radial basis functions with a priori bias and Kriging are chosen to model tool–chip interface temperature and tool wear depth, respectively. The non-dominated solutions are found using the strength Pareto evolutionary algorithm SPEA2 and compared with the non-dominated front obtained from pure simulation-based MOO. The metamodel-based MOO method is not only advantageous in terms of reducing the computational time by 70%, but is also able to discover 31 new non-dominated solutions over simulation-based MOO.