Mahalanobis–Taguchi system applied to variable selection in automotive pedals components using Gompertz binary particle swarm optimization

This work presents the application of the Mahalanobis–Taguchi system (MTS) to variable detection in the manufacturing process of automotive pedals components. The combinatorial optimization problem of variable selection is solved by the application of Gompertz binary particle swarm optimization algorithm. Moreover, a numerical comparison with respect to other common version of binary particle swarm and binary ant colony optimization algorithms is presented followed by a discussion regarding the corresponding numerical results.

► Hybrid Mahalanobis–Taguchi system (MTS) using Gompertz binary PSO (GBPSO) is applied to a injection moulding process in automotive industry.
► First time that GBPSO is combined with MTS.
► A numerical comparison between binary PSO (BPSO), binary ant colony optimization (NBACO) and GBPSO is reported.