Multiobjective Optimization of the Heating Process for Forging Automotive Crankshaft

Abstract

This paper presents potential approaches that increase the energy efficiency of an inline induction heating system for forging of an automotive crankshaft. Both heat loss reduction and optimization of process parameters are proposed scientifically in order to minimize the energy consumption and the temperature deviation in the workpiece. We applied the numerical multiobjective optimization method in conjunction with the design of experiment (DOE), mathematical approximation with metamodel, nondominated sorting genetic algorithm (GA), and engineering data mining. The results show that using the insulating covers reduces heat by an amount equivalent to 9% of the energy stored in the heated workpiece, and approximately 5.8% of the energy can be saved by process parameter optimization.