OPTIMIZATION OF SURFACE GRINDING PARAMETERS ON AISI D2 STEEL USING RESPONSE SURFACE METHODOLOGY

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
Deepak Tripathi ◽  
Milind Dandekar ◽  
Vaibhav Jain
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Grinding ◽  
Aisi D2 Steel ◽  
Grinding Parameters ◽  
Aisi D2 ◽  
D2 Steel

Experimental Study on Microstructure Evolution in AISI D2 Steel Surface Grinding

2011 ◽  
Vol 487 ◽  
pp. 126-130
Author(s):  
L. Yan ◽  
Feng Jiang ◽  
Y.M. Rong
Keyword(s):  
Grain Size ◽  
Microstructure Evolution ◽  
Steel Surface ◽  
White Layer ◽  
Surface Grinding ◽  
Aisi D2 Steel ◽  
Dark Layer ◽  
Grinding Parameters ◽  
Aisi D2 ◽  
D2 Steel

The microstructure evolution of ground subsurface in AISI D2 steel surface grinding was investigated in this study. The effect of grinding parameters and grain size of wheels on white layer formation was presented. The surface integrity parameters of microstructure and microhardness were measured and analyzed. It was found that the white layer and dark layer may occur more easily when using finer grain size of wheel and white layer and dark layer may occur with the increase of grinding parameters, such as wheel rotation speed, workpiece speed and depth of cut.

INVESTIGATION OF EFFECTS OF DIELECTRIC TYPE AND POLARITY ON ELECTRIC DISCHARGE MACHINING OF AISI D2 STEEL USING RESPONSE SURFACE METHODOLOGY

2019 ◽  
Vol XVI (4) ◽  
pp. 81-93
Author(s):  
Muhammad Hanif ◽  
Wasim Ahmad ◽  
Salman Hussain ◽  
Mirza Jahanzaib
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Electric Discharge ◽  
Discharge Current ◽  
Removal Rate ◽  
Electric Discharge Machining ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
D2 Steel

This paper presents a study on optimisation of process parameters of die-sinking electric discharge machining. The influence of dielectric type, electrode polarity, discharge current and gap on the material removal rate (MRR) and surface roughness for machining of AISI D2 steel have been studied. Response surface methodology suggested in the existing literature was employed for conducting the experiments. Kerosene and transformer oils were found as the best dielectric for MRR and surface roughness, respectively. It was also found that electrode with positive polarity offers high MRR while negative polarity ensures best surface finish. ANOVA results indicated that discharge current was the most influencing factor affecting the performance measures, MRR and surface roughness. Although discharge gap showed low effect on MRR and surface roughness, it was effective for debris removal. Empirical models were developed to optimise the results of MRR and surface roughness.

scholarly journals Multi-Objective Optimization for Grinding of AISI D2 Steel with Al2O3 Wheel under MQL

Materials ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2269 ◽  
Author(s):  
Aqib Mashood Khan ◽  
Muhammad Jamil ◽  
Mozammel Mia ◽  
Danil Yurievich Pimenov ◽  
Vadim Rashitovich Gasiyarov ◽  
...  
Keyword(s):  
Flow Rate ◽  
Heat Dissipation ◽  
Cutting Speed ◽  
Surface Grinding ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Aisi D2 Steel ◽  
Multi Objective ◽  
Aisi D2 ◽  
D2 Steel

In the present study, the machinability indices of surface grinding of AISI D2 steel under dry, flood cooling, and minimum quantity lubrication (MQL) conditions are compared. The comparison was confined within three responses, namely, the surface quality, surface temperature, and normal force. For deeper insight, the surface topography of MQL-assisted ground surface was analyzed too. Furthermore, the statistical analysis of variance (ANOVA) was employed to extract the major influencing factors on the above-mentioned responses. Apart from this, the multi-objective optimization by Grey–Taguchi method was performed to suggest the best parameter settings for system-wide optimal performance. The central composite experimental design plan was adopted to orient the inputs wherein the inclusion of MQL flow rate as an input adds addition novelty to this study. The mathematical models were formulated using Response Surface Methodology (RSM). It was found that the developed models are statistically significant, with optimum conditions of depth of cut of 15 µm, table speed of 3 m/min, cutting speed 25 m/min, and MQL flow rate 250 mL/h. It was also found that MQL outperformed the dry as well as wet condition in surface grinding due to its effective penetration ability and improved heat dissipation property.

Evaluation of Deep Criogenic Treatment at Microabrasive Wear of Aisi D2 Steel

2015 ◽  
Vol 1120-1121 ◽  
pp. 1257-1263
Author(s):  
Cosme Roberto Moreira Silva ◽  
Tiago F.O. Melo ◽  
José A. Araújo ◽  
J.L.A. Ferreira ◽  
S.J. Gobbi
Keyword(s):  
Wear Resistance ◽  
Treatment Cycle ◽  
Cryogenic Treatment ◽  
Deep Cryogenic Treatment ◽  
Abrasive Resistance ◽  
Austenitization Temperature ◽  
Aisi D2 Steel ◽  
X Ray ◽  
Aisi D2 ◽  
D2 Steel

Wear resistance of tool steels can be increased with deep cryogenic treatment (DCT) application. Mechanisms related to DCT are still not completely understood. Microabrasive wear resistance of cryogenically treated samples of AISI D2 steel was evaluated in terms of austenitization temperature at heat treatment cycle and quenching steps related to DCT. X-ray difractometry, scanning and optical microscopy and quantitative evaluation of carbides with image analysis were carried out aiming material characterization. For samples subjected to higher austenitization temperatures, the DCT treatment does not increase abrasive wear resistance. For samples treated at lower austenitization temperature, the DCT treatment results on 44% increase at abrasive resistance. This effect is correlated to the increase of the amount of fine carbides distributed at samples matrices cryogenically treated.

Sustainable machining. Modeling and optimization of temperature and surface roughness in the milling of AISI D2 steel

2019 ◽  
Vol 71 (2) ◽  
pp. 267-277 ◽  
Author(s):  
Aqib Mashood Khan ◽  
Muhammad Jamil ◽  
Ahsan Ul Haq ◽  
Salman Hussain ◽  
Longhui Meng ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Empirical Modeling ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Aisi D2 Steel ◽  
Content Type ◽  
Sustainable Machining ◽  
Aisi D2 ◽  
D2 Steel

Purpose Sustainable machining is a global consensus and the necessity to cope up the serious environmental threats. Minimum quantity lubrication (MQL) and nanofluids-based MQL(NFMQL) are state-of-the-art sustainable lubrication modes. The purpose of this study is to investigate the effect of process parameters, such as feed rate, depth of cut and cutting fluid flow rate, on temperature and surface roughness of the manufactured pieces during face milling of the AISI D2 steel. Design/methodology/approach A statistical technique called response surface methodology with Box–Behnken Design was used to design experimental runs, and empirical modeling was presented. Analysis of variance was carried out to evaluate the model’s accuracy and the validation of the applied technique. Findings A comprehensive analysis revealed the superiority of implementing NFMQL in comparison to MQL within the levels of process parameters. The comparison has shown a significant reduction of temperature under NFMQL at the tool-workpiece interface from 16.2 to 34.5 per cent and surface roughness from 11.3 to 12 per cent. Practical implications This research is useful for practitioners to predict the responses in workshop and select appropriate cutting parameters. Moreover, this research will be helpful to reduce the resource which will ultimately save energy consumption and cost. Originality/value To cope with the industrial challenges and tribological issues associated with the milling of AISI D2 steel, experiments were conducted in a distinct machining mode with innovative cooling/lubrication. Until now, few studies have addressed the key lubrication effects of Al2O3-based nanofluid on the machinability of D2 steel under NFMQL lubrication condition.

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