Effect of surface curvature on tribological performance of AISI 1045 steel after multi-scan spot continual induction hardening process

Gao, Kai; Qin, Xunpeng; Zhu, Zhenhua; Chen, Xuliang

doi:10.1016/j.triboint.2017.10.004

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…Sulfur, selenium, copper, lead, aluminium, and calcium are only some of the alloying elements that may be modified in stainless steel during melting in order to tailor the material's machinability [5]. Because of its many high-tech uses, stainless steel is often expected to be tough and scratch-proof [6]. Surface hardness, scratch resistance, and wear resistance may all be increased by the use of procedures that have been proven effective in industry [7].…”

Section: Introductionmentioning

confidence: 99%

Characterization of induction hardened and tempered AISI 1045 steel

Wenish¹,

Prince²,

Maniraj³

2022

Matéria (Rio J.)

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In this investigation of AISI 1045 steel are tested in two stages. In the first stage of AISI 1045 steel samples, induction boriding and induction hardening of heat treatment typically 800 °C, 900 °C, 1000 °C, 1100 °C, and 1200 °C applied over the course of two seconds. Internal strains maybe mitigated using a 30 min tempering at temperature ranges 300 °C, 500 °Cand 700 °C. After that the samples subjected to the induction hardening, microhardness and tensile strength according to ASTM. The lowest hardness readings are achieved between 800 and 1100 °C, while the maximum hardness of 685HV is reported after heating to 1200 °C and then cooling in water. The second stage involves AISI 1045 steel is treated with low-temperature plasma nitro-carburizing, and its effects are studied. The specimens are treated at temperatures over 430 °C, NCr 2 is formed and has an effect on the corrosion resistance property. Increasing the temperature to 450 °C raises the surface hardness to approximately 1000 HV 0.05 . Treatment at 400 °C results in superior corrosion resistance compared to untreated steel. According to the results of the experiments, the surface hardness of AISI 1045 steel materials increases with an increase in temperature.

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Section: Introductionmentioning

confidence: 99%

Characterization of induction hardened and tempered AISI 1045 steel

Wenish¹,

Prince²,

Maniraj³

2022

Matéria (Rio J.)

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“…It can make materials with poor wear resistance adhere to a layer of materials with higher wear resistance, such as 42CrMo steel with high strength, good hardenability, good toughness, and good creep resistance, which is widely used in automobile crankshafts, and mechanical parts such as transmission gears [2] . However, its wear resistance is poor [3] , and T15 powder high-speed steel can be clad to this material to improve its wear resistance [4][5][6] . Laser cladding has the advantages of low dilution rate, small heat-affected zone, small deformation, and metallurgical bonding, and it is widely used in the fields of surface modification and surface repair [7] .…”

Section: Introductionmentioning

confidence: 99%

Data-driven Decision-making Approach of Laser Cladding Parameters for Low Carbon

Zhang

Tang

Zhao

et al. 2022

J. Phys.: Conf. Ser.

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The machining performance, such as carbon emission, dilution ratio rate, and powder utilization rate, can be improved by selecting appropriate process parameters in laser cladding. However, the importance evaluation of machining performance by users is often fuzzy. How to make a reasonable decision about laser cladding parameters under this condition? To resolve the problem, a multi-objective fuzzy decision-making approach of laser cladding parameters is proposed using support vector regression (SVR), multi-objective dragonfly algorithm (MODA), and fuzzy TOPSIS. Firstly, SVR is used to build the correlation model among laser cladding dilution rate, powder utilization rate, carbon emission, and process parameters. Secondly, MODA is applied to search non-dominated process parameters (non-dominated solution) based on the model. Finally, the non-dominated process parameters are sorted by fuzzy TOPSIS according to the user’s evaluation, the process parameter ranking first is the laser cladding process parameters that best meet the requirements of users, and the feasibility and effectiveness of the approach are verified via the experiments. The low-carbon decision-making problem of laser cladding parameters under the fuzzy evaluation can be well solved by the proposed approach.

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