Multi-objective optimization of fixture locating layout for sheet metal part using Kriging and MOBA

Abstract

Owing to the multi-objective attribute and excessive computational burden of finite element analysis (FEA) during the optimization of fixture locating layout, a new multi-objective optimization method for the sheet metal fixture design based on the Kriging surrogate model and multi-objective bat algorithm (MOBA) is proposed in this paper. The fixture locating layout is treated as the design variable while the overall deformation and maximum deformation of sheet metal under its dead weight are treated as the objective functions. The training and testing sample sets are generated by Latin hypercube sampling (LHS) and FEA. Kriging surrogate model is built by learning from the training sample set and the multi-objective optimization model for fixture locating layout is constructed based on the established Kriging surrogate model. MOBA is employed to find Pareto optimal solution set for the sheet metal fixture locating layout. Finally, a bi-objective optimization case of fixture locating layout for the sheet metal part based on the “4-2-1” locating principle is conducted to verify the proposed method.