Optimization of grinding process parameters for slender tubes through orthogonal experiments and grey relational analysis

Slender tubes are serving as crucial components for facilitating the reliable transport of gases and liquids in precision equipment across medical, aviation, and aerospace industries. The smoothness of their inner surfaces improved by reduced surface roughness is essential for ensuring the safe and efficient operation of such equipment. This study delved into the grinding mechanism of composite magnetorheological fluid and developed a material removal rate (MRR) model to identify key grinding process parameters. The influence of these parameters and their interactions on MRR and surface roughness (Sq) was studied, subsequently, the regression model constructed accordingly can predict machining performance. Notably, the optimal parameter combinations for maximizing MRR and minimizing surface roughness were found to be inconsistent. To reconcile this conflict, grey relational analysis (GRA) was applied to transform the multi-objective optimization problem into a single-objective optimization of grey relational grade (GRG), thereby enabling a comprehensive evaluation of grinding performance. A high quality surface with surface roughness Sq of 3.161 μm can be achieved at an material removal rate of 0.0610 μm/min under the condition of the optimized process parameters from grey correlation analysis. Compared with the results obtained by intuitive analysis, using this approach, the comprehensive grinding performance was improved by 42.71% and 32.74%, respectively. This study shows that the grinding process parameters of metal slender tube can be optimized by combinating of orthogonal test and grey correlation analysis, and which provides a new idea for the grinding of metal slender tube.