Papers by Keyword: Surface Grinding

Abstract: 9XC steel is a steel alloy of the commonly used tool to make a variety of products. When manufacturing such products, surface grinding method is commonly used as the final machining method for critical surfaces. Therefore, it is very necessary to research for improving surface quality and machining productivity when grinding this steel. In this study, Multi-Criteria Decision-Making (MCDM) is presented when surface grinding 9XC steel with a segmented grinding wheel. Taguchi method has been chosen to design the experimental matrix. MCDM has been performed using Proximity Indexed Value (PIV). This study has determined the value of workpiece velocity, feed rate and depth of cut to simultaneously ensure the minimum surface roughness and the maximum Material Removal Rate (MRR). The effect of cutting parameters on surface roughness has been also discussed.

Abstract: The joint research of scientists of two countries deals with cylindrical and surface grinding with abrasive wheels of heat-resistant steel Inconel 625 (KhN77TYu GOST 5632 – 72 Russian Federation standard), (analogues include Hastalloy, N07080, Alloy 80A, Nimonic 80A, 2.4952 ASTM B637/ASME SB637, UNS N07080). The article shows the results of studies of the features of high-temperature steel during grinding with a fastened abrasive. The results of experiments are given to determine the optimal characteristics of grinding wheels, grinding modes, cooling-lubricant fluids. Experimental data about geometric accuracy, surface roughness, resistance of wheels are demonstrated as well. The ways to prevent from defects during cylindrical and surface grinding of high-strength steel are proposed. The recommendations to increase the tool resistance and output of the process are given.

Abstract: This article describes an optimization of dressing parameters to improve the wheel life in surface grinding of hardened SKD 11 steel by using the Taguchi method. Dressing parameters including dressing feed rate, coarse dressing depth, coarse dressing times, fine dressing depth, fine dressing times, and non-feeding dressing were investigated to determine their influence on the wheel life. The DOE method developed by G. Taguchi was selected to design the experiments. An analysis of the signal-to-noise (S/N) response and ANOVA were conducted to obtain the optimal values of dressing parameters for maximizing the wheel life. In the results section, the coarse dressing times and the coarse dressing depth are determined to be the most influential factors which give a statistically significant effect on wheel life. Also, a predictive value of the average wheel life is given with a 3.6% deviation from the verification experiment.

Abstract: This study is to determine effects of the dressing parameters to the flatness tolerance (Fl) when grinding SKD11 steel using HaiDuong grinding wheel and also propose the suitable dressing parameters to obtain the smallest flatness tolerance. In this paper, the effects of the six input parameters including feed rate (S), depth of rough dressing cut (a_r), rough dressing times (n_r), depth of finish dressing cut (a_f), finish dressing times (n_f) and non-feeding dressing (n_non) to the flatness tolerance were investigated. To find out the influence of each input parameter on output results, the S/N ratio was analysized. Evaluated experimental results show that, the average flatness tolerance was 4.05μm and deviation of this value was 11.38% compared with the predicted value.

Abstract: This paper presents an optimization of dressing conditions for SKD-11 steel grinding using HaiDuong grinding wheel made in Vietnam. Taguchi method was used to design experiment and calculate the optimized dressing conditions. Effects of the six input parameters including feed rate (S), depth of rough dressing cut (a_edr), rough dressing times (n_r), depth of finish dressing cut (a_edf), finish dressing times (n_f) and non-feeding dressing (n_non) with 4 levels on the machined surface roughness were investigated for optimization process. To find out the influence degree of each input parameter on output results, S/N ratio was analysized. Experimental results show that the average surface roughness after 3 times of the repeated experiments was 0.208 μm and deviation was 11.23% comparing with the predicted values.

Abstract: This paper introduces a study on multi-criteria optimization of the dressing parameters in surface grinding for 90CrSi tool steel. The aim of the study is to minimize the surface roughness, the normal shear force and maximize the grinding wheel life by using Taguchi method and Grey Relational Analysis (GRA). This multi-objective optimization is obtained by optimizing four four-level and two two-level dressing parameters in sixteen experiments based on an orthogonal array L₁₆(4⁴×2²). From the results of the study, the optimum dressing parameters were proposed. Also, to evaluate the optimum dressing model, an experiment was performed. The results of the comparison between the predicted model and the experiment show that the proposed model has been proven and it can be used for further applying of surface grinding.

Abstract: This paper aims to investigate the effect of process parameters on the surface roughness in suface grinding 90CrSi tool steel. In this paper, many process parameters including the coolant concentration, the coolant flow, the cross feed, the table speed and the depth of cut were taken into account. Based on conducting and analysing 2⁵ experiments which were created by using full factorial design, the influence of the process parameters on the surface roughness was evaluated. Also, a predicted model to calculate the surface roughness was proposed.

Abstract: This study aims to propose a method to calculate optimum exchanged grinding wheel diameter to minimize grinding cost in grinding surface process for stainless steel. The interactions of the grinding cost and optimum exchanged grinding wheel diameter have been analyzed and presented in mathematical formulae. To obtain the minimal grinding cost, the optimal exchanged grinding wheel diameter has been determined by investigating six two-level grinding process parameters including initial grinding wheel diameter, total dressing depth, radial grinding wheel wear per dress, wheel life, machine tool hour and grinding wheel cost. Based on 2⁶ experiments conducted in computational program, the optimal exchanged grinding wheel diameter is presented as a function of these grinding parameters. This developed model has been verified and proven by experimental results. The proposed method of calculation of the optimum exchanged grinding wheel diameter can be applied in practice to reduce the grinding cost.

Abstract: Visualization of work surface topography through simulations is very challenging task in grinding process due to the complexity of wheel-work interactions with a very high number of cutting points (grits). Kinematic mapping of abrasive grits on a three-dimensional wheel topography enables the evaluation of ground surface topography through simulations. In this paper, a method for generating the ground surface topography based on wheel specifications is presented. Abrasive grits size, abrasives volume percentage and their nature of distribution on the wheel surface are considered in the modeling and visualization of wheel topography. The simulation results of ground surface topographies prove the feasibility of the developed method.

Abstract: In striving to remain competitive in the global market, the concept of optimization of manufacturing processes has been extensively employed to meet the diverse production requirements. Optimization analysis of machining processes is usually based on either minimizing or maximizing certain objective functions. Recently, various non-traditional optimization techniques have evolved to optimize the process parameters of machining processes. The objective of this work is to study the effectiveness of the most commonly used non-traditional optimization methods as applied to a particular machining optimization problem. In this work, surface grinding processes are optimized using i) Particle Swarm Optimization (PSO) ii) Adaptive Genetic Algorithm (AGA) iii) Simulated Annealing (SA) and iv) Memetic algorithm (MA). Memetic algorithm used here has two variations as MA-1 and MA-2, each having the combination of PSO and SA and AGA and SA respectively. The mathematical model of surface grinding operations was adopted from a literature. A computer program was written in Visual C++ for the optimization computations. The computation results of various optimization methods are compared and it is observed that the results of PSO method have outperformed the results of other methods in terms of the combined objective function (COF).