Modeling and Optimization of the Cutting Parameters in Scroll Machining based on RSM and Desirability Function

• RSM-based models predict surface roughness, cutting force, and material removal rate. • Multi-objective optimization with desirability function balances quality, energy, and productivity. • Optimal machining parameters provide guidance for high-quality and efficient in scroll machining. The processing quality of scrolls is vital to the overall performance of scroll compressors. However, improving processing quality often leads to increased energy consumption and reduced productivity. To balance these competing factors, this study aims to identify optimal cutting parameters and evaluate their effects on surface roughness, cutting force, and material removal rate in scroll machining. A multi-objective optimization approach is proposed, employing response surface methodology (RSM) combined with the desirability function (DF) technique. The study begins with a series of machining experiments designed based on a four-factor, five-level experimental setup. Predictive models for surface roughness, cutting force, and material removal rate are then developed using RSM, and their statistical significance is rigorously assessed through Analysis of Variance (ANOVA) and Pareto analysis. The influence of cutting parameters on machining responses is thoroughly analyzed, providing insights into the scroll machining process. Finally, optimization is performed using the DF across four objectives: processing quality optimization, energy consumption optimization, productivity optimization and a combined quality-energy-productivity optimization. The optimal machining parameters identified for multi-objective optimization are a depth of cut of 3.00 mm, feed rate of 0.05 mm/z, cutting speed of 4000 r/min, and radial depth of cut of 1.00 mm. This study provides practical guidance for achieving high-quality scroll machining while maintaining energy efficiency and productivity.