scholarly journals Multi-Objective Optimization for Grinding Parameters of 20CrMnTiH Gear with Ceramic Microcrystalline Corundum

Materials ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1352 ◽  
Author(s):  
Shengyong Zhang ◽  
Genbao Zhang ◽  
Yan Ran ◽  
Zhichao Wang ◽  
Wen Wang
Keyword(s):  
Surface Roughness ◽  
Practical Significance ◽  
Grinding Wheel ◽  
Linear Regression Method ◽  
Grinding Process ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Grinding Parameters ◽  
The Impact

(1) The alloy material 20CrMnTiH is widely used in gear manufacturing, but difficult to process, and its quantity (efficiency) and quality (surface quality) are generally negative correlation indicators. As a difficult but realistic problem, it is of important practical significance to explore how to efficiently grind high-precision low-carbon alloy gear workpieces. (2) Firstly, the pixel method was applied to analyze the grinding principles and explore the grinding parameters—the grinding wheel speed and grinding wheel frame moving speed—as well as the feed rate, which impacts the grinding indicators. Secondly, based on the ceramic microcrystalline corundum grinding wheel and the 20CrMnTiH gear workpiece, controlled experiments with 28 groups of grinding parameters were conducted. Moreover, the impact curves of the grinding parameters on the grinding indicators—the grinding efficiency, grinding wheel life, and surface roughness—were obtained by the multiple linear regression method. Finally, the multi-objective optimization method was used to comprehensively optimize the grinding process. (3) Compared with the traditional grinding process, under optimized grinding parameters, the 20CrMnTiH gear workpieces have a lower surface roughness and a longer grinding wheel life, and require a shorter time to achieve grinding accuracy. (4) The grinding experiments showed that the grinding parameters are linearly related to the grinding indicators. The optimization results show that the precision, efficiency, and economy of the 20CrMnTiH gear grinding process have been improved via the comprehensive optimization of the grinding parameters.

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

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 893
Author(s):  
Nguyen Anh Tuan
Keyword(s):  
Surface Roughness ◽  
Alloy Steel ◽  
Process Parameters ◽  
Machining Process ◽  
Multi Objective Optimization ◽  
The Real ◽  
Multi Objective ◽  
Fine Grinding ◽  
Centerless Grinding ◽  
The Impact

In this article, new research on the multi-objective optimization of the process parameters applied to enhance the efficiency in the shoe-type centerless grinding operation for the inner ring raceway of the ball bearing made from SUJ2 alloy steel is presented. The four important input parameters for this process, which included the normal feed rate of fine grinding (Snf), the speed of the workpiece (Vw), the cutting depth of fine grinding (af), and the number of ground parts (Np), were investigated. The aim of the study was to find the most appropriate value set of process parameters in order to, simultaneously minimize the grindstone wear (Gw), maximize the material removal rate (MRR) and the total number of ground parts in a grinding cycle (N’p), while guaranteeing other technology requirements such as surface roughness Ra ≤ 0.5 (µm), oval level Op ≤ 3 (µm), etc. In order to solve the problem, based on the experimental data, in which the grindstone wear was measured online by a measuring system consisting of two pneumatic probes, the optimization of the target functions of Gw, N’p, and MRR and mathematical models that express the dependencies of outcome parameters Gw, Ra, Op, MRR, etc. on the process parameters were determined. Therefore, a global optimal solution of such a discrete and nonlinear multi-objective optimization problem was solved by using a genetic algorithm, presenting the most appropriate process parameters as follows: Snf = 15.38 (µm/s), Vw = 6.00 (m/min), af = 11.76 (µm), and Np = 20 (parts/cycle). In addition, the impact of the four process parameters (Snf, Vw, af, Np) on the wear of the grinding wheel (Gw), the oval level of parts (Op), and the surface roughness of parts (Ra) was evaluated. The discovered technology mode has been applied to the real machining process for the inner ring raceway of the 6208_ball bearing made from SUJ2 alloy steel, and the outcome showed a much better result in comparison with default setting modes, while still ensuring the technology requirements. The difference between the predicted values and the real values of the parameters Gw, Ra, Op, and MRR were controlled within 5% of the ranges.

scholarly journals Combining Taguchi method and DEAR method for multi-objective optimization of grinding process

2021 ◽  
Vol 309 ◽  
pp. 01220
Author(s):  
Do Duc Trung ◽  
Nguyen Huu Quang ◽  
Dang Quoc Cuong ◽  
Nguyen Hong Linh ◽  
Nguyen Van. Tuan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Removal Rate ◽  
Cutting Speed ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Pareto Chart ◽  
Multi Objective ◽  
Input Parameters ◽  
Experimental Process

In this paper, a study on multi-objective optimization of the cylindrical grinding process is presented. The experimental material used in this study is X12M steel. The two output parameters of the grinding process considered in this study are surface roughness and material removal rate (MRR). The cutting mode parameters including cutting speed, feed rate, and cutting depth have been selected as input parameters of the experimental process. Experimental matrix by Taguchi method has been used to design a matrix with 27 experiments. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. The Data Envelopment Analysis-based Ranking (DEAR) method has been applied to determine the values of input parameters to simultaneously ensure the two criteria of minimum surface roughness and maximum MRR. Finally, the development direction for further studies has also been recommended in this study.

scholarly journals COMBINATION OF TAGUCHI METHOD, MOORA AND COPRAS TECHNIQUES IN MULTI-OBJECTIVE OPTIMIZATION OF SURFACE GRINDING PROCESS

2020 ◽  
pp. 1-9
Author(s):  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Optimization Problem ◽  
Removal Rate ◽  
Optimization Techniques ◽  
Surface Grinding ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Multi Objective

This study presentes a combination method of several optimization techniques and Taguchi method to solve the multi-objective optimization problem for surface grinding process of SKD11 steel. The optimization techniques that were used in this study were Multi-Objective Optimization on basis of Ratio Analysis (MOORA) and Complex Proportional Assessment (COPRAS). In surface grinding process, two parameters that were chosen as the evaluation creterias were surface roughness (Ra) and material removal rate (MRR). The orthogonal Taguchi L16 matrix was chosen to design the experimental matrix with two input parameters namely workpiece velocity and depth of cut.  The two optimization techniques that mentioned above were applied to solve the multi-objective optimization problem in the grinding process. Using two above techniques, the optimized results of the cutting parameters were the same. The optimal workpiece velocity and cutting depth were 20 m/min and 0.02 mm. Corresponding to these optimal values of the workpiece velocity and cutting depth, the surface roughness and material removal rate were 1.16 µm and 86.67 mm3/s. These proposed techniques and method can be used to improve the quality and effectiveness of grinding processes by reducing the surface roughness and increasing the material removal rate.

Regression Modeling of Surface Roughness in Grinding

2011 ◽  
Vol 271-273 ◽  
pp. 34-39 ◽  
Author(s):  
Ilhan Asiltürk ◽  
Levent Çelik ◽  
Eyüb Canli ◽  
Gürol Önal
Keyword(s):  
Surface Roughness ◽  
Manufacturing Sector ◽  
Depth Of Cut ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Important Indicator ◽  
Manufacturing Method ◽  
Grinding Parameters ◽  
Reliable Model ◽  
Art Industry

Grinding is a widely used manufacturing method in state of art industry. By realizing needs of manufacturers, grinding parameters must be carefully selected in order to maintain an optimum point for sustainable process. Surface roughness is generally accepted as an important indicator for grinding parameters. In this study, effects of grinding parameters to surface roughness were experimentally and statistically investigated. A complete factorial experimental flow was designed for three level and three variable. 62 HRC AISI 8620 cementation steel was used in grinding process with 95-96% Al2O3 grinding wheel. Surface roughness values (Ra, Rz) were measured at the end of process by using depth of cut, feed rate and workpiece speed as input parameters. Experimental results were used for modeling surface roughness values with linear, quadric and logarithmic regressions by the help of MINITAB 14 and SPSS 16 software. The best results according to comparison of models considering determination coefficient were achieved with quadric regression model (84.6% for Ra and 89% for Rz). As a result, a reliable model was developed in grinding process which is a highly complex machining operation and depth of cut was determined as the most effective parameter on grinding by variance analysis (ANOVA). Obtained theoretical and practical acquisitions can be used in various areas of manufacturing sector in the future.

scholarly journals The Influence of Crystal Orientation on Subsurface Damage of Mono-Crystalline Silicon by Bound-Abrasive Grinding

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 365
Author(s):  
Wei Yang ◽  
Yaguo Li
Keyword(s):  
Surface Roughness ◽  
Crystal Orientation ◽  
Subsurface Damage ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Diamond Grit ◽  
Peripheral Speed ◽  
Damage Depth ◽  
The Impact ◽  
Subsurface Defects

Subsurface damage (SSD) produced in a grinding process will affect the performance and operational duration of single-crystal silicon. In order to reduce the subsurface damage depth generated during the grinding process by adjusting the process parameters (added), experiments were designed to investigate the influence of machining factors on SSD. This included crystal orientation, diamond grit size in the grinding wheel, peripheral speed of the grinding wheel, and feeding with the intention to optimize the parameters affecting SSD. Compared with isotropic materials such as glass, we considered the impact of grinding along different crystal directions <100> and <110> on subsurface damage depth (added). The Magnetorheological Finishing (MRF) spot technique was used to detect the depth of SSD. The results showed that the depth of SSD in silicon increased with the size of diamond grit. SSD can be reduced by either increasing the peripheral speed of the grinding wheel or decreasing the feeding rate of the grinding wheel in the <100> crystal orientation, if the same size of diamond grit was employed. In addition, we proposed a modified model around surface roughness and subsurface crack depth, which considered plastic and brittle deformation mechanisms and material properties of different crystal orientations. When the surface roughness (RZ) exceeded the brittle-plastic transition’s critical value RZC (RZC<100> > 1.5 μm, RZC<110> > 0.8 μm), cracks appeared on the subsurface. The experimental results were consistent with the predicted model, which could be used to predict the subsurface cracks by measuring the surface roughness. However, the model only gives the approximate range of subsurface defects, such as dislocations. The morphology and precise depth of plastic deformation subsurface defects, such as dislocations generated in the fine grinding stage, needed to be inspected by transmission electron microscopy (TEM), which were further studied.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

scholarly journals Study on the Effect of Grinding Pressure on Material Removal Behavior Performed on a Self-Designed Passive Grinding Simulator

2021 ◽  
Vol 11 (9) ◽  
pp. 4128
Author(s):  
Peng-Zhan Liu ◽  
Wen-Jun Zou ◽  
Jin Peng ◽  
Xu-Dong Song ◽  
Fu-Ren Xiao
Keyword(s):  
Residual Stress ◽  
Surface Roughness ◽  
Service Life ◽  
Material Removal ◽  
Removal Rate ◽  
Grinding Force ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Grinding Temperature ◽  
Grinding Efficiency

Passive grinding is a new rail grinding strategy. In this work, the influence of grinding pressure on the removal behaviors of rail material in passive grinding was investigated by using a self-designed passive grinding simulator. Meanwhile, the surface morphology of the rail and grinding wheel were observed, and the grinding force and temperature were measured during the experiment. Results show that the increase of grinding pressure leads to the rise of rail removal rate, i.e., grinding efficiency, surface roughness, residual stress, grinding force and grinding temperature. Inversely, the enhancement of grinding pressure and grinding force will reduce the grinding ratio, which indicates that service life of grinding wheel decreases. The debris presents dissimilar morphology under different grinding pressure, which reflects the distinction in grinding process. Therefore, for rail passive grinding, the appropriate grinding pressure should be selected to balance the grinding quality and the use of grinding wheel.

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