The effect of multiple pass cutting on surface integrity when hard turning of AISI D2 cold work tool steel

2007 ◽  
Vol 1 (1) ◽  
pp. 97 ◽  
Author(s):  
M.A. Kamely ◽  
M.Y. Noordin ◽  
V.C. Venkatesh
2009 ◽  
Vol 24 (12) ◽  
pp. 1373-1382 ◽  
Author(s):  
V. N. Gaitonde ◽  
S. R. Karnik ◽  
Luis Figueira ◽  
J. Paulo Davim

2005 ◽  
Vol 169 (3) ◽  
pp. 388-395 ◽  
Author(s):  
J.G. Lima ◽  
R.F. Ávila ◽  
A.M. Abrão ◽  
M. Faustino ◽  
J. Paulo Davim

Author(s):  
Ahmad Kamely Mohamad ◽  
Noordin Mohd Yusof ◽  
Ali Ourdjini ◽  
Vellore Chelvaraj Venkatesh

2013 ◽  
Vol 577 ◽  
pp. S726-S730 ◽  
Author(s):  
Edgar Apaza Huallpa ◽  
J. Capó Sánchez ◽  
L.R. Padovese ◽  
Hélio Goldenstein

2014 ◽  
Vol 13 (04) ◽  
pp. 237-246 ◽  
Author(s):  
Pijush Samui

This paper adopts Minimax Probability Machine Regression (MPMR), Multivariate Adaptive Regression Spline (MARS), and Least Square Support Vector Machine (LSSVM) for prediction of surface and hole quality in drilling of AISI D2 cold work tool steel with uncoated titanium nitride (TiN) and titanium aluminum nitride (TiAlN) monolayer- and TiAlN/TiN multilayer-coated-cemented carbide drills. MPMR is a probabilistic model. MARS is a nonparametric regression technique. LSSVM is developed based on statistical learning algorithm. Cutting tool (t), Feed rate (fr)(mm/rev), and Cutting speed (v)(m/min) have been adopted as inputs of MPMR, MARS, and LSSVM. The output of MPMR, MARS, and LSSVM is Surface roughness (rs) (μm) and Roundness error (re) (μm). A comparative study has been presented between the developed models. The results show that the developed model gives excellent performance.


Author(s):  
M. Ahmadi Najafabadi ◽  
J. Teymuri Shandi

Acoustic emission (AE) has been known as an excellent technique to monitor crack propagation and fracture mechanism. For more domination on AE behavior of materials, comprehensive knowledge on effective parameters is necessary. Heat treatment as one of the important factors on AE characteristics of a material must be considered. This investigation is primarily aimed at studying the effect of tempering heat treatment on characteristics of acoustic emission signals monitored during tension tests of a cold-work tool steel. Single edge notched samples of AISI D2 cold-work tool steel were prepared. Then, respectively annealing, austenitizing and tempering were performed. Tempering was carried out at 5 different temperatures from 0 to 575 C. Finally, samples were loaded at tension and AE signals recorded synergistically. Analyzing of the characteristics of AE signals showed that: (a) In all tempering conditions, the AECC increases slowly at the beginning and rapidly at the point of crack growth, although at higher tempering temperatures we have gradual rise in AECC plot; (b) Increasing tempering temperature, average value of AE count number, amplitude, energy and peak frequency decreases; (c) At 525 C, because of secondary hardening, average value of investigated AE parameters increase strongly and (d) analyzing the relation between fracture mode, AE characteristics and tempering temperature showed that special AE behavior of specimens tempered at 525 C is because of the transformation of retained austenite in ferritic matrix.


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