Optimization of Replaced Grinding Wheel Diameter for Surface Grinding Based on a Cost Analysis

Abstract

Based on a cost analysis, a method of identifying and predicting optimum replaced grinding wheel diameter (De.op) in a surface grinding operation for 9CrSi steel material was developed in this study. The De.op value was determined by minimizing the cost function. An experimental design was set up, and a computational program was developed to perform the experiment in order to calculate the De.op value. Furthermore, the impact of the grinding process parameters such as the initial grinding wheel diameter, the grinding wheel width, the total dressing depth, the Rockwell hardness of the workpiece, the radial grinding wheel wear per dress, and the wheel life on the De.op value were investigated. Moreover, the impacts of the cost components such as the machine tool hourly rate and the grinding wheel cost on the De.op value were given. Based on that, a mathematical model was proposed to determine the De.op value. The predicted De.op value was also verified by an experiment. The obtained result shows that the difference between the experimental De.op value and the predicted De.op value is within 1.7%, indicating that the mathematical model proposed in the study is reliable.

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

“…In those studies, the researchers have focused on different targets over different value sets of variables in specific applications. However, the previous studies have focused primarily on the optimization of cutting parameters under surface grinding [5][6][7][8][9][10][11] and cylindrical grinding [12][13][14]. In 2002, based on the genetic algorithm, R. Saravanan et al [5] developed an optimization procedure using a multi-objective function model with a weighted approach and predefined mathematical models of constraints to optimize grinding conditions in the surface grinding process.…”

“…In 2018, Aqib Mashood Khan et al [7] optimized the process parameters to receive the best surface finish, minimum forces, and temperature in the surface grinding process for AISI D2 steel with an Al 2 O 3 wheel under minimum quantity lubrication. In 2019, based on the analysis of the grinding cost per part, the optimization problem of the replaced grinding wheel diameter in a surface grinding operation for 9CrSi steel material was studied to minimize the grinding cost [8]. A methodology was proposed for computing the optimal cutting parameters to maximize the material removal rate in the cylindrical grinding process for EN45 steel materials [14].…”

Effect of Dressing Parameters on Material Removal Rate when Surface Grinding SKD11 Tool Steel

“…Improving the efficiency of the grinding process has been increasingly demanded. However, the typical elements of the grinding process are influenced by many factors such as the work-piece, the grinding machine, the grinding wheel, and process parameters settings [1][2][3][4][5][6][7][8]. These factors not only affect directly on the cutting capacity of grinding wheel, but also impact on the process performance, the accuracy and the quality of ground parts.…”

Optimizing Dressing Conditions for Minimum Flatness Tolerance when Grinding SKD11 Tool Steel

“…And the output parameters normally are surface rougness, wheel life, productivity and tolerance. Optimum researches are often performed for different grinding methods which include external grinding [5][6][7][8], internal grinding [9][10][11][12] or surface grinding [13][14][15][16]. In a study, the influence of the input grinding parameters when grinding table punches using CBN grinding wheel on CNC milling machine was investigated and the optimum values were also determined.…”