scholarly journals Study on Thixojoining Process Using Partial Remelting Method

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
M. N. Mohammed ◽  
M. Z. Omar ◽  
M. S. Salleh ◽  
K. S. Alhawari

Cold-work tool steel is considered to be a nonweldable metal due to its high percentage content of carbon and alloy elements. The application of a new process of the semisolid joining of two dissimilar metals is proposed. AISI D2 cold-work tool steel was thixojoined to 304 stainless steel by using a partial remelting method. After thixojoining, microstructural examination including metallographic analysis, energy dispersive spectroscopy (EDS), and Vickers hardness tests was performed. From the results, metallographic analyses along the joint interface between semisolid AISI D2 and stainless steel showed a smooth transition from one to another and neither oxides nor microcracking was observed. Hardness values obtained from the points in the diffusion zone were much higher than those in the 304 stainless steel but lower than those in the AISI D2 tool steel. The study revealed that a new type of nonequilibrium diffusion interfacial structure was constructed at the interface of the two different types of steel. The current work successfully confirmed that avoidance of a dendritic microstructure in the semisolid joined zone and high bonding quality components can be achieved without the need for force or complex equipment when compared to conventional welding processes.

2014 ◽  
Vol 663 ◽  
pp. 276-280
Author(s):  
M.N. Mohammed ◽  
Mohammed Zaidi Omar ◽  
Junaidi Syarif ◽  
Zainuddin Sajuri ◽  
M. Shukor Salleh ◽  
...  

Cold-work tool steel is considered to be a nonweldable metal due to its high percentage content of carbon and alloying elements. The application of a new process of the semi-solid joining of two parts of AISI D2 cold-work tool steel is proposed using a partial remelting method. Samples were heated in an argon atmosphere up to 1275°C which corresponded to about 20% of liquid fraction and held for 10 minutes. Metallographic analyses along the joint interface showed a smooth transition from one to the other and neither oxides nor micro-cracking was observed. The current work successfully confirmed that avoidance of a dendritic microstructure in the semi-solid joined zone and high bonding quality components can be achieved without the need for force or complex equipment when compared to conventional welding processes.


2014 ◽  
Vol 217-218 ◽  
pp. 355-360 ◽  
Author(s):  
M.N. Mohammed ◽  
Mohd Zaidi Omar ◽  
Junaidi Syarif ◽  
Zainuddin Sajuri ◽  
Mohd Shukor Salleh ◽  
...  

Cold-work tool steel is considered to be a non-weldable metal due to its high percentage content of carbon and alloying elements. To address this problem the application of a new process of semisolid joining using a direct partial remelting method was developedto achieve a spherical join structure between two parts of AISI D2 cold-work tool steel. Since the surface oxidation of this metalis very high, the control of the atmosphere during joining had to be considered. Samples were heated in an argon atmosphere at two different temperatures of 1250°C and 1275°C for 10 minutes. Metallographic analyses along the joint interface showed that an increase in temperature promoted the final joining properties and also that at a liquid fraction of 15% joining was not fully practicable. However, a20% liquid fraction can produce a very good joint and microstructure as compared to the other experimental liquid fraction. Metallographic analyses along the joint interface showed a smooth transition from one to the other and neither oxides nor microcracking was observed. The current work confirmed that avoidance of a dendritic microstructure in the semisolid joined zone and high bonding quality components can be achieved without the need for force or complex equipment when compared to conventional welding processes.


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

2019 ◽  
Vol 285 ◽  
pp. 115-120
Author(s):  
Mohammed N. Abdul Razaq ◽  
M. Zaidi Omar ◽  
Salah Al-Zubaidi ◽  
Khaled S. Alhawari ◽  
Mnel A. Abdelgnei

The application of hybrid structures or components made of dissimilar metal offers the potential to utilize the advantages of different materials often providing unique solutions to engineering requirements. However, the joining of materials by conventional welding techniques becomes difficult if the physical properties such as melting temperature and thermal expansion coefficients of the two materials are different. In this study, a new process of joining semi-solid AISI D2 tool steel and AISI 304 stainless steel using a partial remelting method is proposed. Moreover, the effect of the holding time on the microstructural evolution was investigated. The processing temperatures for the thixojoining was 1320°C and held for 5, 12, 20 and 30 minutes, respectively. The results obtained from investigating the basic geometries demonstrated a good joining quality that differs from the conventional process of welding. Metallographic analyses along the joint interface between semi-solid AISI D2 and 304 stainless steel showed a smooth transition from one to the other, with neither oxides nor microcracking being observed.


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.


2013 ◽  
Vol 265 ◽  
pp. 653-662 ◽  
Author(s):  
N. Yasavol ◽  
A. Abdollah-zadeh ◽  
M. Ganjali ◽  
S.A. Alidokht

Author(s):  
Pijush Samui ◽  
H. Yildirim Dalkilic

This chapter examines the capability of Gaussian Process Regression (GPR) and Relevance Vector Machine (RVM) for prediction of surface and hole quality in drilling of AISI D2 cold work tool steel. This chapter uses GPR and RVM as regression techniques. The database contains information about cutting tool, feed rate, cutting speed, surface roughness, and roundness error. Cutting tool, feed rate, and cutting speed are considered inputs of GPR and RVM. The outputs of GPR and RVM are surface roughness and roundness error. In RVM, radial basis function is adopted as kernel function. GPR uses radial basis function as covariance function. The obtained variance can be used to determine uncertainty. A sensitivity analysis is also carried out. This chapter gives robust models based on RVM and GPR for prediction of surface and hole quality in drilling of AISI D2 cold work tool steel.


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