Modeling and optimization of high-grade compacted graphite iron milling force and surface roughness via response surface methodology

作者：Lin Yongchuan; Huang Jianyou^*; Wei Jueyu; Liao Xiaoping; Xiao Zeqing

来源：Australian Journal of Mechanical Engineering, 2018, 16(1): 50-57.

DOI：10.1080/14484846.2017.1296531

• Compacted graphite iron
• Cutting forces
• Machining efficiency
• Modeling and optimization
• Parameter optimisation
• Response surface method
• Response surface methodology
• Roughness predictions

In this study, RuT400(σb ≥ 500 MPa) was milled with different cutting speeds, feeding rates and cutting depths to construct cutting force and surface roughness prediction models via response surface method (RSM). The milling parameters were optimised via response surface, contour map and iterative algorithm. The results show that that feeding rate and cutting depth are factors that significantly affect the cutting force. Similarly, cutting speed and feeding rate were found to be significant in regards to surface roughness. The multivariate linear equations yield more accurate surface roughness and cutting force predictions than fitting the linearised multivariate non-linear equations. The cutting force prediction model is F = 60.823 − 0.020V + 149.489f + 41.932a;the surface roughness prediction model is Ra = 1.633 − 0.00161V + 1.803f + 0.0289a. The use of high-strength tools and a high-endurance manufacturing system for cutting force can greatly enhance the machining efficiency in a processing system with favourable rigidity.

• 出版日期2018
• 单位广西大学