scholarly journals Modelling and analysis of tool wear and surface roughness in hard turning of AISI D2 steel using response surface methodology

2018 ◽  
pp. 63-74 ◽  
Author(s):  
M. Junaid Mir ◽  
M. F. Wani
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Tool Wear ◽  
Response Surface ◽  
Hard Turning ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
D2 Steel

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 Experimentation on Tool Wear and Surface Roughness in AISI D2 Steel Turning with WC Insert

2018 ◽  
Vol 08 (03) ◽  
pp. 204-220 ◽  
Author(s):  
N. López-Luiz ◽  
O. Jiménez Alemán ◽  
F. Alvarado Hernández ◽  
M. Montoya Dávila ◽  
V. H. Baltazar-Hernández
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
Steel Turning ◽  
D2 Steel

scholarly journals Modelling of Flank wear, Surface roughness and Cutting Temperature in Sustainable Hard Turning of AISI D2 Steel

2018 ◽  
Vol 20 ◽  
pp. 406-413 ◽  
Author(s):  
Ramanuj Kumar ◽  
Ashok Kumar Sahoo ◽  
Rabin Kumar Das ◽  
Amlana Panda ◽  
Purna Chandra Mishra
Keyword(s):  
Surface Roughness ◽  
Wear Surface ◽  
Hard Turning ◽  
Flank Wear ◽  
Cutting Temperature ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
D2 Steel

DEVELOPMENT OF SURFACE ROUGHNESS PREDICTION MODEL FOR HARD TURNING ON AISI D2 STEEL USING CUBIC BORON NITRIDE INSERT

2017 ◽  
Vol 80 (1) ◽  
Author(s):  
Amrifan Saladin Mohruni ◽  
Muhammad Yanis ◽  
Edwin Kurniawan
Keyword(s):  
Surface Roughness ◽  
Boron Nitride ◽  
Feed Rate ◽  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Aisi D2 Steel ◽  
Aisi D2 ◽  
D2 Steel

Hard turning is an alternative to traditional grinding in the manufacturing industry for hardened ferrous alloy material above 45 HRC. Hard turning has advantages such as lower equipment cost, shorter setup time, fewer process steps, greater part geometry flexibility and elimination of cutting fluid. In this study, the effect of cutting speed and feed rate on surface roughness in hard turning was experimentally investigated. AISI D2 steel workpiece (62 HRC) was machined with Cubic Boron Nitride (CBN) insert under dry machining. A 2k-factorial design with 4 centre points as an initial design of experiment (DOE) and a central composite design (CCD) as augmented design were used in developing the empirical mathematical models. They were employed for analysing the significant machining parameters. The results show that the surface roughness value decreased (smoother) with increasing cutting speed. In contrary, surface roughness value increased significantly when the feed rate increased. Optimum cutting speed and feed rate condition in this experiment was 105 m/min and 0.10 mm/rev respectively with surface roughness value was 0.267 µm. Further investigation revealed that the second order model is a valid surface roughness model, while the linear model cannot be used as a predicted model due to its lack of fit significance.

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