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Surface performance is an important indicator of the performance of cold roll-beating spline processing. To obtain the best cold roll spline surface performance (surface roughness, residual stress, and surface hardening degree), multiobjective optimal process parameters must be determined. To this end, this paper takes the cold roll-beating spline as the object of study and carries out a cold roll-beating spline surface performance test study. An ideal algorithm for entropy weight is constructed, and the multiobjective decision of the cold roll-beating spline surface performance is determined by using the entropy weight ideal point algorithm, providing a decision on the cold roll-beating spline processing parameters. The grey correlation algorithm is used for verification, and the results show that the multiobjective decision of the cold roll-beating spline surface performance is feasible by using the constructed entropy weight ideal point algorithm.

Surface Performance Multiobjective Decision of a Cold Roll-Beating Spline with the Entropy Weight Ideal Point Method