Tailoring Wear Properties of Nodular Cast Iron through Induction Hardening Optimization

Abstract The current study investigated the wear performances of GGG60 nodular cast iron under different loads after induction hardening at different powers and durations. The background of this study is the optimization of induction hardening parameters applied to increase the wear resistance of GGG60 nodular cast iron, which is the raw material of parts subjected to high wear loads such as crankshafts, gear systems and flywheels. With the obtained wear results, the induction parameters were optimized by RSM. Induction hardening was treated at four induction powers and two induction durations. Wear tests were conducted using the ball-on-disc method under dry wear conditions for 60 min. Three different wear loads of 10, 20, and 30 N were used. The samples were analyzed in terms of microstructure, hardness, and wear characterization. Subsequently, a RSM model was constructed using the wear results Untreated specimens have significantly lower performance characteristics than treated ones. The hardness, penetration depth, and wear performance indicated a strong relationship with the increase in both induction power and duration. The optimization model presented that the most critical parameter of volume loss is the wear load. In addition, induction power and wear load were found to be significant in the wear rate. The model's prediction capacity for volume loss is satisfactory. Nevertheless, the model's prediction capacity for the wear rate experienced a slight decrease. Conclusions indicate the model can estimate the induction hardening parameters.

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Publication Details

Journal
International Journal of Metalcasting
Published
2025-01-27
DOI
https://doi.org/10.1007/s40962-025-01548-0
Citations
1
Primary Topic
Metal Alloys Wear and Properties
Type
article
Field-Weighted Citation Impact
0.52
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article

Tailoring Wear Properties of Nodular Cast Iron through Induction Hardening Optimization

Okan Ünal, İsmail Aykut Karamanlı
1 citations
International Journal of Metalcasting
Metal Alloys Wear and Properties
0.52
article

Tailoring Wear Properties of Nodular Cast Iron through Induction Hardening Optimization

Okan Ünal, İsmail Aykut Karamanlı
article en
1 citations

Abstract

Abstract The current study investigated the wear performances of GGG60 nodular cast iron under different loads after induction hardening at different powers and durations. The background of this study is the optimization of induction hardening parameters applied to increase the wear resistance of GGG60 nodular cast iron, which is the raw material of parts subjected to high wear loads such as crankshafts, gear systems and flywheels. With the obtained wear results, the induction parameters were optimized by RSM. Induction hardening was treated at four induction powers and two induction durations. Wear tests were conducted using the ball-on-disc method under dry wear conditions for 60 min. Three different wear loads of 10, 20, and 30 N were used. The samples were analyzed in terms of microstructure, hardness, and wear characterization. Subsequently, a RSM model was constructed using the wear results Untreated specimens have significantly lower performance characteristics than treated ones. The hardness, penetration depth, and wear performance indicated a strong relationship with the increase in both induction power and duration. The optimization model presented that the most critical parameter of volume loss is the wear load. In addition, induction power and wear load were found to be significant in the wear rate. The model's prediction capacity for volume loss is satisfactory. Nevertheless, the model's prediction capacity for the wear rate experienced a slight decrease. Conclusions indicate the model can estimate the induction hardening parameters.

International Journal of MetalcastingVol. 19(6)
Karabük University (TR), Yozgat Bozok Üniversitesi (TR)
Openalex Percentile: Top 42%
Metal Alloys Wear and Properties
0.52
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Tailoring Wear Properties of Nodular Cast Iron through Induction Hardening Optimization — Okan Ünal, İsmail Aykut Karamanlı · International Journal of Metalcasting (2025) | TGRS Research Map | TGRS