Multi-objective parametric optimization for high surface quality and process efficiency in micro-grinding

In this study, for the selection of maximum material removal rate and minimum surface roughness [Formula: see text] in micro-grinding of aluminum alloy through multi-response optimization, two optimization approaches are proposed based on statistical analysis and genetic algorithm. The statistical analysis–based approach applies response surface methodology according to the analysis of variance to propose a mathematical model for [Formula: see text]. In addition, the individual desirability of material removal rate, [Formula: see text], and the global desirability function are calculated, and the inverse analysis is conducted to locate input setting giving maximum desirability function. The genetic algorithm–based approach uses the improved multi-objective particle swarm optimization with the experimental data trained by support vector machine. To demonstrate that the material microstructure is a significant parameter for material removal rate and [Formula: see text], the models with and without Taylor factor consideration are developed and compared. The optimized results achieved from both response surface methodology and improved multi-objective particle swarm optimization demonstrate that the consideration of Taylor factor can significantly improve the optimization process to achieve the maximum material removal rate and minimum [Formula: see text].

Optimization of Cutting Parameters in Machining GFRP Using End Mill Cutter through DoE and Verification through Genetic Algorithm

This article discusses optimization of critical parameters such as cutting speed, feed, depth of cut and method of machining while machining Glass Fiber Reinforced Plastic (GFRP) in vertical machining center using standard end mill cutter made up of High Speed Steel (HSS) for lesser cutting load, maximum material removal rate for better surface finish and dimensional accuracy through design of experiments. In composite material machining, surface finish is the critical deciding factor in determining surface quality. In this study, as per Taguchi’s L9 orthogonal array, predictable and unpredictable parts are followed to evaluate the consequence of cutting parameters on the machined component. The study includes surface roughness measurement using surface profilometer continued by physical measurement of machined pocket dimension. The experimental results, suggest suitable machining parameters in order to achieve the above target goal. In addition, C++ program is developed to cross check the most favorable machining parameters for maximum material removal rate using genetic algorithm. It is inferred from the study that the genetic algorithm results coincides very closely with the result given by the method of design of experiments.

An Experimental Study on Grinding Fir-Tree Root Forms Using Vitrified CBN Wheels

An experimental study was undertaken to explore the conditions and performance on rough and finish grinding fir-tree root forms of turbine blades made of a nickel-based alloy using vitrified CBN wheels and water-based grinding fluid. This work was motivated by switching the grinding of fir-tree root forms from grinding with conventional abrasive wheels to vitrified CBN wheels for reducing overall production cost and enhancing productivity. Grinding experiments were conducted to measure grinding forces, power, surface roughness, and stress near the blade roots under various dressing and grinding conditions. Wheel re-dressing life in terms of the total number of good parts ground between dressing was tested with the condition producing the maximum material removal rate while satisfying preset part quality and process requirements. It was found that the maximum material removal rate achievable in rough grinding was restricted by the stress limit and the wheel re-dressing life was dominated by the radial wheel wear limit. The targeting part quality and process requirements were achieved. It was proved that vitrified CBN grinding process is feasible and very promising to machine fir-tree root forms.

The Mechanism of Polymer Particles in Silicon Wafer CMP

In order to increase the material removal rate of silicon wafer, composite abrasives slurry was used in CMP. Zeta potential of polymer particle was measured and interaction potential energy between silica abrasives and polymer particles in slurry were analyzed and calculated. Adsorptions between silica abrasives and polymer particles were observed with TEM. CMP experiments had been taken to analyze the effects of polishing parameters (the concentration of colloidal silica and polymer particle, the pressure and the speed of polishing) on the material removal rate. The mechanism of polymer particle in polishing was elaborated. Experimental results indicated that PS, PMMA and BGF polymer particles could adsorb silica abrasives in slurry. Silica shell/PS core, silica shell/PMMA core and silica shell/BGF core particles could be used to formulate composite abrasives slurries. The material removal rate with composite abrasives slurry was higher than that of single abrasive slurry. The maximum material removal rate was obtained with silica shell/BGF core composite abrasives slurry.