Surface work-hardening optimization of cold roll-beating splines based on an improved double-response surface-satisfaction function method

• Main Authors: Fengkui Cui, Yongxiang Su, Xiaoqiang Wang, Xiang Yu, Xiaolin Ruan, Libo Liu
• Format: Article
• Language: English
• Published: SAGE Publishing 2018-06-01
• Series: Advances in Mechanical Engineering
• Online Access: https://doi.org/10.1177/1687814018782630

The work hardening of a spline during cold roll-beating is used as an indicator to evaluate the mechanical properties of the surface. To further optimize the work-hardening degree of a cold roll-beating spline surface, weight theory and satisfaction functions are used to improve the double-response surface-satisfaction function model. The model describes the involute spline based on the cold roll-beating speed and feed rate. The generalized reduced-order gradient method is applied to optimize the optimal combination of processing parameters. The experiments validate the optimization results of the improved double-response surface-satisfaction function method and the conventional response surface method based on the cold roll-beating spline test and a comparative analysis of the spline surface metallographic structure. The results show that the satisfaction degree of the improved response model is 0.87384, indicating that the model is robust and reliable. The optimized processing parameters are a cold roll speed of 1448.21 r/mm, a feed rate of 41.71 mm/min, and a degree of work hardening of 144.79%. The spline surface work-hardening degree based on the revised model is higher than that of the conventional model. Thus, the improved double-response surface-satisfaction function model provides better accuracy.