The Effect of Holding Time of Deep Cryogenic-Treated AISI D3 Cutting Tool on Machinability of Low Carbon Steels Using Taguchi’s Technique

2020 ◽  
Vol 19 (02) ◽  
pp. 215-233
Author(s):  
Satish Kumar ◽  
Mohan Nagraj ◽  
R. Suresh ◽  
Arunkumar Bongale ◽  
Nitin Khedkar

This paper deals with the effect of machining parameters on tool wear, surface roughness and cutting forces in dry turning of low carbon steel with deep cryo-treated AISI D3 tool steel. AISI D3 tool steel was used for preparation of cutting tools as per International Standard Organization (ISO: 3685-1993). Deep cryogenic treatment ([Formula: see text]C) of D3 tool steel was carried out at different holding time (12[Formula: see text]h, 24[Formula: see text]h and 36[Formula: see text]h) followed by tempering at [Formula: see text]C for 2[Formula: see text]h. Taguchi’s L27 orthogonal array is used for optimizing the process parameters during machining process. Analysis of variance (ANOVA) was carried out to study the significance of the input parameters. Mathematical models were developed using linear regression analysis for validating results. The tool worn surface shows the abrasion wear and oxidation wear were the main wear mechanisms observed under higher speed and feed rate cutting conditions.

2014 ◽  
Vol 592-594 ◽  
pp. 2513-2517
Author(s):  
S.P. Sivapirakasham ◽  
S. Thiyagarajan ◽  
Jose Mathew ◽  
M. Surianarayanan ◽  
A.S. Sathya Sai Nathan

Emission of toxic substances is the major occupational and environmental problem associated with this process. These emissions may cause adverse health effects to the operators and has the direct impact on the environment. The present investigation was conducted to study together the environmental and machining aspects of EDM process. The work aims to investigate the emission and machining parameters in EDM process using different workpiece material viz; like aluminum, mild steel and AISI-D3 tool steel with EDM 30 as a dielectric fluid and brass as a electrode. The results showed that the aluminium workpiece material gave a higher emission rate and MRR compared with mild steel and AISI D3 tool steel due to the low melting and boiling temperature. Among the process parameters, peak current and pulse duration was found to strongly affect the emission and performance aspects.


Author(s):  
Y. Arslan ◽  
I. Uygur ◽  
A. Jazdzewska

Recently, deep cryogenic treatment is performed to improve the mechanical responses (wear, hardness, fatigue, and thermal conductivity) of various steel components. Researchers have tried to evaluate the eco-friendly and nontoxic process to optimize the parameters. Cold-shearing punches used to manufacture various holes that undergo severe impact loading and wear in the metal forming process. This study concerns the effect of soaking time (24 hr, 36 hr) at liquid nitrogen temperature (−145 °C) during the deep cryogenic treatment on the microstructural changes which are carbide distribution and retained austenite percentage of AISI D3 tool steel punches. It was shown that the deep cryogenic treatment reduces retained austenite and enhanced uniform distribution of carbide particles. It is concluded that for significantly improved punch life and performance, it is an advisable application of 36 hr deep cryogenic treatment.


Friction ◽  
2015 ◽  
Vol 3 (3) ◽  
pp. 234-242 ◽  
Author(s):  
Nay Win Khun ◽  
Erjia Liu ◽  
Adrian Wei Yee Tan ◽  
D. Senthilkumar ◽  
Bensely Albert ◽  
...  

2013 ◽  
Vol 330 ◽  
pp. 747-753
Author(s):  
Othman Belgassim ◽  
Abdurahman Abu-Saada

This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulse current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg . Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used.


2016 ◽  
Vol 63 (1) ◽  
pp. 45-71 ◽  
Author(s):  
S. Prabhu ◽  
B. K. Vinayagam

Abstract Electrical Discharge Machining (EDM) process with copper tool electrode is used to investigate the machining characteristics of AISI D2 tool steel material. The multi-wall carbon nanotube is mixed with dielectric fluids and its end characteristics like surface roughness, fractal dimension and metal removal rate (MRR) are analysed. In this EDM process, regression model is developed to predict surface roughness. The collection of experimental data is by using L9 Orthogonal Array. This study investigates the optimization of EDM machining parameters for AISI D2 Tool steel using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Analysis of variance (ANOVA) and F-test are used to check the validity of the regression model and to determine the significant parameter affecting the surface roughness. Atomic Force Microscope (AFM) is used to capture the machined image at micro size and using spectroscopy software the surface roughness and fractal dimensions are analysed. Later, the parameters are optimized using MINITAB 15 software, and regression equation is compared with the actual measurements of machining process parameters. The developed mathematical model is further coupled with Genetic Algorithm (GA) to determine the optimum conditions leading to the minimum surface roughness value of the workpiece.


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