Improvement of Adhesive Wear Behavior by Variable Heat Treatment of a Tool Steel for Sheet Metal Forming

González-Pociño, Alejandro; Álvarez-Antolín, Florentino; Lozano, José Antonio Flórez

doi:10.3390/ma12172831

Cited by 15 publications

(6 citation statements)

References 15 publications

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“…Podgornik et al [8] investigated the influence of the surface preparation condition of forming tool steel with PVD coatings (TiN, TiB 2 , TaC, and WC/C) on galling properties. Gonzalez-Pociño et al [9] confirmed the heat treatment parameters (quenching, tempering, and nitriding process) that significantly affect adhesive wear resistance through an experiment in which these parameters were deliberately changed. Ogunbiyi et al [10] suggested that the wear performance of Inconel 738 low-carbon composites could be enhanced with the addition of graphene nanoplatelets.…”

Section: Introductionmentioning

confidence: 96%

Efficient Wear Simulation Methodology for Predicting Nonlinear Wear Behavior of Tools in Sheet Metal Forming

et al. 2022

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In conventional wear simulation, the geometry must be updated for succeeding iterations to predict the accumulated wear. However, repeating this procedure up to the desired iteration is rather time consuming. Thus, a wear simulation process capable of reasonable quantitative wear prediction in reduced computational time is needed. This study aimed to develop an efficient wear simulation method to predict quantitative wear reasonably in reduced computational time without updating the geometry for succeeding iterations. The wear resistance of a stamping tool was quantitatively evaluated for different punch shapes (R3.0 and R5.5) and coating conditions (physical vapor deposition of CrN and AlTiCrN coatings) by using a progressive die set. To capture the nonlinear wear behavior with respect to strokes, a nonlinear equation from a modified form of Archard’s wear model was proposed. By utilizing the scale factor representing the changes in wear properties with respect to wear depth as input, the simulation can predict the behavior of rapidly increasing wear depth with respect to strokes after failure initiation. Furthermore, the proposed simulation method is efficient in terms of computational time because it does not need to perform geometry updates.

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Section: Introductionmentioning

confidence: 96%

Efficient Wear Simulation Methodology for Predicting Nonlinear Wear Behavior of Tools in Sheet Metal Forming

et al. 2022

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“…To achieve this, times of permanence at the austenitising temperature need to be above 4 h [ 11 ]. Destabilisation of the austenite increases the Ms temperature, thus decreasing the percentage of retained austenite [ 12 , 13 ]. During tempering, a secondary hardening could be produced due to the precipitation of carbides of the types M 7 C 3 and M 23 C 6 , associated with Cr [ 9 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Optimisation of Thermal Processes with Plasma Nitriding on Vanadis 4 High Speed Steel

et al. 2022

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Vanadis 4 steel is a tool steel processed by powder metallurgy (PM). Its main alloying elements are Cr, V and Mo. Through the application of a design of experiments with six factors and eight experiments, the parameters of the process related to the thermal treatment of these steels are deliberately varied. Those thermal parameters related to the destabilisation of austenite were analysed: the cooling method in quenching, tempering and the application of an ionic nitriding treatment. Through XRD, the percentage and types of precipitated crystalline phases were determined, and, through SEM-EDX, the microstructure was revealed. At the same time, through a pin-on-disc test, those factors with a significant influence on resistance to wear were determined. It has been concluded that, in order to increase resistance to wear, treatments of destabilisation of the austenite at 900 °C with oil quenching, tempering at 550 °C for 4 h and a subsequent treatment of plasma nitriding would be very favourable. This tempering favours a second destabilisation of the austenite and its transformation into martensite, as well as the joint precipitation of type M7C3 and MC carbides. The thickness of the nitrided layer exceeds 100 microns and generates a fully adhesive wear mechanism.

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“…For example, D2, O1, and A1 are cold work tool steel, and H11, H13, and H21 are hot work tool steel under AISI standards. These tool steels are heat-treated to obtain the required properties for the particular application (Kheirandish et al 2010;Lesyk et al 2017;Huber et al 2019;Deirmina et al 2019;Gonzalez-Pociño et al 2019;Kumar et al, 2021a); sometimes, the heat-treated tool steels nitrided to improve the surface properties (Díaz-Guillén et al 2020;Miyamoto et al 2019;Fathallah et al 2019;Díaz-Guillén et al 2018;Abreu et al 2020;Podgornik et al 2012). The production can be run without any interruption.…”

Section: Introductionmentioning

confidence: 99%

Application of integrated BWM Fuzzy-MARCOS approach for coating material selection in tooling industries

Kumar

Maity

Patnaik

2021

Preprint

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The life of metal forming dies, and the efficiency of tooling industries depends on the mechanical and wear properties of tool steel. These properties can be further improved by depositing the ceramic coating on heat-treated tool steel. There are many coating materials available with numerous excellent properties. But problem is how to select the best coating material. Compared to various studies related to material selection problems in the contrasting area of utilization, remarkably, few research work is done in tooling industries. In the present work, we have identified eight coating materials (alternatives) and nine evaluation criteria under the consultation of an expert in the tooling application and tribological field. To deal with this coating material selection problem, an integrated fuzzy-MADM method is proposed comprising BWM and fuzzy-MARCOS. This integrated fuzzy-MADM method is used to evaluate the alternative, and the obtained results are scrutinized under extensive use of sensitivity analysis. In the first phase of analysis, seven scenarios of criteria weight change are used, which is derived by the BWM method; dynamic matrices are used in the second phase of analysis. In the third and fourth phases, obtained ranks are compared with those obtained by different weight calculation methods and ranking methods, respectively. All the phases have similar results, i.e., AlCrN/TiAlN coating (alternative Cm5) is the best coating material. What is more, the proposed method has been used to solve the published results of coating material selection. To evaluate its reliability and robustness, a four phases comparative sensitivity analysis was performed.

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Improvement of Adhesive Wear Behavior by Variable Heat Treatment of a Tool Steel for Sheet Metal Forming

Cited by 15 publications

References 15 publications

Efficient Wear Simulation Methodology for Predicting Nonlinear Wear Behavior of Tools in Sheet Metal Forming

Efficient Wear Simulation Methodology for Predicting Nonlinear Wear Behavior of Tools in Sheet Metal Forming

Optimisation of Thermal Processes with Plasma Nitriding on Vanadis 4 High Speed Steel

Application of integrated BWM Fuzzy-MARCOS approach for coating material selection in tooling industries

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