Modeling and optimization of machining parameters during grinding of flat glass using response surface methodology and probabilistic uncertainty analysis based on Monte Carlo simulation

Abstract In this paper, the performance of diamond grinding wheels was investigated. The industrial diamond crystals with a size of 140/170 mesh were utilized. The microstructure of the grinding tool was observed using a Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Analysis Device (EDX). The experiments were designed using Box–Behnken method and optimum grinding parameters for glass were analytically determined. Experimental studies were carried out on a surface grinding machine in a flat glass factory. Grinding characteristics were examined with respect to surface roughness. The effects of grinding parameter on output responses were studied using analysis of variance (ANOVA). Probabilistic uncertainty analysis depends on Monte Carlo simulation was applied. Moreover, after the experiments using the optimized cutting parameters, the microstructure of the grinding wheels was analyzed. From results, the established model and optimization method could be employed for predicting surface roughness and this work is reliable and suitable for solving the problems encountered in machining operations. The lifetime of Cu-based grinding discs can be increased by adding Zn and Fe to the matrix material.

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