A Study on Optimization of Surface Roughness in Surface Grinding 9CrSi Tool Steel by Using Taguchi Method

2018 ◽  
pp. 100-108 ◽  
Author(s):  
Luu Anh Tung ◽  
Vu Ngoc Pi ◽  
Do Thi Thu Ha ◽  
Le Xuan Hung ◽  
Tien Long Banh
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Surface Grinding

scholarly journals An analysis of frictional coefficient and surface roughness in surface grinding of SKD 11 tool steel using Minimum Quantity Lubrication (MQL) and dry techniques

2021 ◽  
Vol 1034 (1) ◽  
pp. 012100
Author(s):  
M. Khoirul Effendi ◽  
Bobby O. P. Soepangkat ◽  
Rachmadi Noorcahyo ◽  
I Made Londen Batan ◽  
Arif Wahyudi ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Steel ◽  
Frictional Coefficient ◽  
Minimum Quantity Lubrication ◽  
Surface Grinding ◽  
Minimum Quantity

Optimization of Dressing Parameters in Surface Grinding SKD11 Tool Steel by Using Taguchi Method

2020 ◽  
pp. 636-647
Author(s):  
Tran Thi Hong ◽  
Nguyen Thanh Tu ◽  
Nguyen Anh Tuan ◽  
Tran Ngoc Giang ◽  
Nguyen Thi Quoc Dung ◽  
...  
Keyword(s):  
Taguchi Method ◽  
Tool Steel ◽  
Surface Grinding

scholarly journals Experimental Study on The Effect of Cross Feed of Surface Grinding on the Vibration and the Surface Roughness of Hardened Tool Steel OCR12VM

2020 ◽  
Vol 11 (3) ◽  
pp. 313-322
Author(s):  
Chairul Anam ◽  
◽  
Khairul Muzaka ◽  
Dian Ridlo Pamuji
Keyword(s):  
Surface Roughness ◽  
Tool Steel ◽  
Dimensional Accuracy ◽  
Surface Grinding ◽  
Machining Process ◽  
Depth Of Cut ◽  
Grinding Process ◽  
Hardened Tool Steel ◽  
Stone Type ◽  
Grinding Stone

The grinding process is a machining process to obtain qualified surface roughness levels and high dimensional accuracy. There are two types of processes in the grinding process, namely the roughening and finishing processes. The vibration effect of the roughing process can damage and shorten the life of the tool/machine, while in the finishing process, the effect of vibration will reduce the dimensional accuracy, shape, and surface smoothness of the workpiece. This study aims to determine the effect of crossfeed on the amplitude of vibration and surface roughness of the workpiece on the surface grinding process. The materials used are hardened tool steel OCR12VM with a variety of grinding stone types A46QV and A80LV made of aluminum oxide. The Variables of process parameters are crossfeed (mm / step) and depth of cut (mm). The measurement of vibrations uses an accelerometer, which is processed by the math CAD program in the form of amplitude and frequency. For surface roughness measurements, it is used the MT-301 surface test with 5 sample points and a sample length of 0.8 mm. The results show that the greater the cross-feed value, the bigger the amplitude of the vibration level and the surface roughness of the workpiece. The magnitude of the amplitude of the vibration on the acceleration that occurs in the grinding stone type A46QV starts from 6,7369 -18.7525 g.rms, while the grinding stone type A80LV starts from 5.0904 g.rms to 18.2821 g.rms. The surface roughness achieved in both grit 46 and grit 80 is from N3 to N5.

Effects of Process Parameters on Material Removal Rate and Surface Roughness in Wedm of H-13 Die Tool Steel

2018 ◽  
Vol 28 ◽  
pp. 55-66 ◽  
Author(s):  
Kuldeep Singh ◽  
Khushdeep Goyal ◽  
Deepak Kumar Goyal
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Pulse On Time ◽  
Pulse Off Time

In research work variation of cutting performance with pulse on time, pulse off time, wire type, and peak current were experimentally investigated in wire electric discharge machining (WEDM) process. Soft brass wire and zinc coated diffused wire with 0.25 mm diameter and Die tool steel H-13 with 155 mm× 70 mm×14 mm dimensions were used as tool and work materials in the experiments. Surface roughness and material removal rate (MRR) were considered as performance output in this study. Taguchi method was used for designing the experiments and optimal combination of WEDM parameters for proper machining of Die tool steel (H-13) to achieve better surface finish and material removal rate. In addition the most significant cutting parameter is determined by using analysis of variance (ANOVA). Keywords Machining, Process Parameters, Material removal rate, Surface roughness, Taguchi method

Multi-Criteria Optimization of Dressing Parameters for Surface Grinding 90CrSi Tool Steel Using Taguchi Method and Grey Relational Analysis

2020 ◽  
Vol 998 ◽  
pp. 61-68 ◽  
Author(s):  
Tran Thi Hong ◽  
Nguyen Van Cuong ◽  
Le Hong Ky ◽  
Quoc Tuan Nguyen ◽  
Banh Tien Long ◽  
...  
Keyword(s):  
Taguchi Method ◽  
Tool Steel ◽  
Grey Relational Analysis ◽  
Surface Grinding ◽  
Grinding Wheel ◽  
Multi Objective Optimization ◽  
Relational Analysis ◽  
Proposed Model ◽  
Predicted Model ◽  
Grey Relational

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.

scholarly journals Optimization of Dressing Parameters for Minimum Surface Roughness and Maximum Material Removal Rate in Internal Grinding of SKD11 Tool Steel

2021 ◽  
Vol 309 ◽  
pp. 01165
Author(s):  
Nguyen Anh Tuan ◽  
Do The Vinh ◽  
Pham Duc Lam ◽  
Le Hoang Anh ◽  
Trinh Kieu Tuan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Signal To Noise Ratio ◽  
Internal Grinding ◽  
Grey Relation

This paper introduces a study on multi-objective optimization of dressing parameters in internal grinding of SKD 11 tool steel using Grey based Taguchi method. The L27 orthogonal array of the Taguchi method was selected to design the experiments. The input parameters of the dressing process are the depth of fine, the time of fine dressing, the depth of coarse dressing, the time of coarse dressing, non-feeding dressing, and dressing feed rate. The output factors are surface roughness (SR) and material removal rate (MRR). A grey relation grade was determined by using the signal-to-noise ratio. The ANOVA was applied to find out the effect of input factors on the grey relation grade. In conclusion, the fine dressing times is the parameter that has the strongest impact on multiple performance characteristics, followed by the coarse dressing times. Also, the optimum dressing parameters to get minimum SR and maximum MRR is the depth of coarse dressing of 0.03mm, the time of coarse dressing of 2 times, the depth of fine dressing of 0.01 mm, the time of fine dressing of 2 times, non-feeding dressing of 2 times, and dressing feed rate of 1.2mm/min.

Effect of Process Parameters on Surface Roughness in Surface Grinding of 90CrSi Tool Steel

2020 ◽  
Vol 305 ◽  
pp. 191-197 ◽  
Author(s):  
Tran Thi Hong ◽  
Nguyen Van Cuong ◽  
Le Hong Ky ◽  
Luu Anh Tung ◽  
Thanh Tu Nguyen ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Factorial Design ◽  
Tool Steel ◽  
Process Parameters ◽  
Full Factorial Design ◽  
Surface Grinding ◽  
Depth Of Cut ◽  
Predicted Model ◽  
Full Factorial ◽  
Table Speed

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.

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