The Effect of Manganese Phosphate Coating Corrosion Behaviour at AISI 4140 Steel and Grey Cast Irons Used in Camshaft Production

Electrically melted and over-heated (>1500 °C) grey cast iron at less than 0.04%S, as commonly used, solidifies large amounts of carbides and/or undercooled graphite, especially in thin wall castings; this is necessary to achieve a stronger inoculation. The efficiency of Ce-bearing FeSi alloy is tested for lower ladle addition rates (0.15 and 0.25 wt.%), compared to the base and conventional inoculated iron (Ba,Ca-bearing FeSi alloy). The present work explores chill and associated structures in hypoeutectic grey iron (3.6–3.8%CE, 0.02%S, (%Mn) × (%S) = 0.013–0.016, Alres < 0.002%), in wedge castings W1, W2 and W3 (ASTM A 367, furan resin sand mould), at a lower cooling modulus (1.1–3.5 mm) that is typically used to control the quality of thin wall iron castings. Relatively clear and total chill well correlated with the standard thermal (cooling curve) analysis parameters and structural characteristics in wedge castings, at different wall thickness, displayed as the carbides/graphite ratio and presence of undercooled graphite morphologies. The difference in effects of the two inoculants addition is seen as the ability to decrease the amount of carbides and undercooled graphite, with Ce-bearing FeSi alloy outperforming the conventional inoculant, especially as the wall thickness decreased. It appears that Ce-bearing FeSi alloy could be a solution for low sulphur, electric melt, thin wall iron castings production.

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An assessment of hardness, impact strength, and hot corrosion behaviour of friction-welded dissimilar weldments between AISI 4140 and AISI 304

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-007-1266-7 ◽

2007 ◽

Vol 39 (7-8) ◽

pp. 679-689 ◽

Cited By ~ 32

Author(s):

N. Arivazhagan ◽

Surendra Singh ◽

Satya Prakash ◽

G. Madhusudhan Reddy

Keyword(s):

Impact Strength ◽

Hot Corrosion ◽

Corrosion Behaviour ◽

Aisi 304 ◽

Aisi 4140

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

Surface Review and Letters ◽

10.1142/s0218625x13500339 ◽

2013 ◽

Vol 20 (03n04) ◽

pp. 1350033 ◽

Cited By ~ 1

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.

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