Weld quality and productivity of AISI 4140 steel welded by unpulsed and pulsed GMAW

2018 ◽  
Vol 60 (2) ◽  
pp. 149-155 ◽  
Author(s):  
Turhan Kursun ◽  
Tanju Teker
Keyword(s):  
Weld Quality ◽  
Aisi 4140 Steel ◽  
Aisi 4140

MODELING AND INVESTIGATION OF THE WEAR RESISTANCE OF SALT BATH NITRIDED AISI 4140 VIA ANN

2013 ◽  
Vol 20 (03n04) ◽  
pp. 1350033 ◽  
Author(s):  
ŞERAFETTIN EKINCI ◽  
AHMET AKDEMIR ◽  
HUMAR KAHRAMANLI
Keyword(s):  
Wear Resistance ◽  
Friction Coefficient ◽  
Surface Characterization ◽  
Wear Behavior ◽  
Surface Hardness ◽  
Salt Bath ◽  
Back Propagation Algorithm ◽  
Aisi 4140 Steel ◽  
Aisi 4140 ◽  
Sliding Distance

Nitriding is usually used to improve the surface properties of steel materials. In this way, the wear resistance of steels is improved. We conducted a series of studies in order to investigate the microstructural, mechanical and tribological properties of salt bath nitrided AISI 4140 steel. The present study has two parts. For the first phase, the tribological behavior of the AISI 4140 steel which was nitrided in sulfinuz salt bath (SBN) was compared to the behavior of the same steel which was untreated. After surface characterization using metallography, microhardness and sliding wear tests were performed on a block-on-cylinder machine in which carbonized AISI 52100 steel discs were used as the counter face. For the examined AISI 4140 steel samples with and without surface treatment, the evolution of both the friction coefficient and of the wear behavior were determined under various loads, at different sliding velocities and a total sliding distance of 1000 m. The test results showed that wear resistance increased with the nitriding process, friction coefficient decreased due to the sulfur in salt bath and friction coefficient depended systematically on surface hardness. For the second part of this study, four artificial neural network (ANN) models were designed to predict the weight loss and friction coefficient of the nitrided and unnitrided AISI 4140 steel. Load, velocity and sliding distance were used as input. Back-propagation algorithm was chosen for training the ANN. Statistical measurements of R2, MAE and RMSE were employed to evaluate the success of the systems. The results showed that all the systems produced successful results.

Low-temperature gas nitriding of AISI 4140 steel accelerated by LaFeO3 perovskite oxide

2019 ◽  
Vol 466 ◽  
pp. 989-999 ◽  
Author(s):  
Xing Chen ◽  
Xiangyun Bao ◽  
Yang Xiao ◽  
Chengsong Zhang ◽  
Lina Tang ◽  
...  
Keyword(s):  
Low Temperature ◽  
Perovskite Oxide ◽  
Aisi 4140 Steel ◽  
Gas Nitriding ◽  
Aisi 4140

Effect of TiCN and AlCrN Coating on Tribological Behaviour of Plasma-nitrided AISI 4140 Steel

2017 ◽  
Vol 5 (2) ◽  
pp. 1-17
Author(s):  
Santosh Vitthal Bhaskar ◽  
Hari Narayan Kudal
Keyword(s):  
Physical Vapor Deposition ◽  
Sliding Wear ◽  
Plasma Nitriding ◽  
Titanium Carbonitride ◽  
Wear Behaviour ◽  
Dry Sliding Wear ◽  
Tribological Behaviour ◽  
Wear Properties ◽  
Aisi 4140 Steel ◽  
Aisi 4140

In the present article, samples made of AISI 4140 steel, pre-treated with plasma nitriding (PN), and coated with different coatings like Titanium Carbonitride (TiCN), Aluminium Chromium Nitride (AlCrN), using Physical Vapor Deposition (PVD) technique, were investigated in terms of their microhardness, surface roughness, and dry sliding wear behaviour. Wear tests were performed with a pin-on-disc machine. Coatings were deposited on plasma nitrided samples. The wear behaviour, and wear mechanisms of TiCN- and AlCrN-coated, PN treated AISI 4140 specimens were investigated using a field emission Scanning Electron Microscope (SEM), equipped with an Energy Dispersive X-ray (EDX) analyzer. An SEM was used to study the surface morphology of the worn surfaces. Also, adhesion tests were conducted to investigate the adhesion quality of the coated specimens. The results of the investigation showed improved wear properties. Furthermore, the compound layer formed during nitriding was found to act as an intermediate hard layer, leading to superior sliding wear properties.

scholarly journals Experimental Investigation and Statistical Approach to Wear Characterization of Plasma Nitrided AISI 4140 Steel-A Case Study

2017 ◽  
Vol 15 (1-2) ◽  
Author(s):  
Santosh V. Bhaskar ◽  
Hari N. Kudal
Keyword(s):  
Plasma Nitriding ◽  
Interaction Effects ◽  
Wear Volume ◽  
Effective Parameters ◽  
Operational Parameters ◽  
Sliding Speed ◽  
Aisi 4140 Steel ◽  
Study Results ◽  
Aisi 4140 ◽  
The Impact

<p>Components of forming tool dies such as draw ring, ejector pin use AISI 4140 as material for their manufacturing. The integrity of the die cutting tools is essential to achieve adequate product quality. In present study, the influence of plasma nitriding (PN) on the wear behav-iour of AISI 4140 steel was investigated. Full factorial experimental design technique was used to study the main effects and the interaction effects between operational parameters and the response variable. The control factors at their two levels (-1 and +1) were: applied load (4.905N and 14.715N), sliding speed (3.14 m/s and 5.23 m/s), and sliding distance (500m and 1000m).The parameters were coded as A, B, and C, consecutively, and were investigated at two levels (-1 and +1). Response selected was Wear Volume Loss (WVL). The effects of in-dividual variables and their interaction effects for dependent variables, namely, WVL were determined. The process of selecting significant factors, based on statistical tools, is illustrat-ed. Analysis of Variance (ANOVA) was performed to know the impact of individual factors on the WVL. Untreated and PN treated AISI 4140 specimens were investigated using field emission Scanning Electron Microscope (SEM) equipped with Energy Dispersive X-ray (EDX) analyzer. Finally diagnostics tools were used to check adequacy of the model in terms of assumptions of ANOVA. ‘Design Expert-7’ and ‘Minitab 17’ softwares were used in the study. Results of statistical analysis indicate that the most effective parameters in the WVL were load and sliding speed. The interaction between load and sliding speed was the most influencing interaction. Results of regression analysis indicate regression coefficient (R2) to be above 90% which suggests good predictability of the model. ‘Predicted-R2’ and ‘Adjusted-R2’, found to be in good agreement with R2, for both the materials under investigation. More-over, results of SEM microscopy suggest PN to be an effective technique to reduce wear.</p>

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