Multi-Layer Wear and Tool Life Calculation for Forging Applications Considering Dynamical Hardness Modeling and Nitrided Layer Degradation

Behrens, Bernd‐Arno; Brunotte, Kai; Wester, Hendrik; Rothgänger, Marcel; Müller, Felix

doi:10.3390/ma14010104

Cited by 8 publications

(10 citation statements)

References 24 publications

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“…These tests determined the effect of heat on the tempering of individual material layers in the nitrided surface layer of forging tools. Recent studies confirm the significance of tempering effect on the wear of hot forging tools [19]. Therefore, the following results are up-to-date and expected in the scientific community.…”

Section: Resultsmentioning

confidence: 57%

Advanced Complex Analysis of the Thermal Softening of Nitrided Layers in Tools during Hot Die Forging

2021

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This article is devoted to the issues of thermal softening of materials in the surface layer of forging tools. The research covers numerical modeling of the forging process, laboratory tests of tempering of nitrided layers, and the analysis of tempering of the surface layer of tools in the actual forging process. Numerical modeling was supported by measuring the temperature inside the tools with a thermocouple inserted into the tool to measure the temperature as close to the surface as possible. The modeling results confirmed the possibility of tempering the die material. The results of laboratory tests made it possible to determine the influence of temperature on tempering at different surface layer depths. Numerical analysis and measurement of surface layer microhardness of tools revealed the destructive effect of temperature during forging on the tempering of the nitrided layer and on the material layers located deeper below the nitrided layer. The results have shown that in the hot forging processes carried out in accordance with the adopted technology, the surface layer of working tools is overheated locally to a temperature above 600 °C and tempering occurs. Moreover, overheating effects are visible, because the surface layer is tempered to a depth of 0.3 mm. Finally, such tempering processes lead to a decrease in the die hardness, which causes accelerated wear because of the abrasion and plastic deformation. The nitriding does not protect against the tempering phenomenon, but only delays the material softening process, because tempering occurs in the nitrided layer and in the layers deeper under the nitrided layer. Below the nitrided layer, tempering occurs relatively quickly and a soft layer is formed with a hardness below 400 HV.

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Section: Resultsmentioning

confidence: 57%

Advanced Complex Analysis of the Thermal Softening of Nitrided Layers in Tools during Hot Die Forging

2021

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“…While the conventional Archard model considers the tool hardness as constant, current literature agrees that cyclic thermomechanical loading to the surface leads to extensive changes of microstructure and hardness of the layer during the running production [78,79]. With regard to a data-driven modelling of this phenomenon, a test methodology was developed at the Institute of Metal Forming and Forming Machines (IFUM) to realistically replicate this load accumulation using a forming dilatometer to later analyze the resulting changes in the hardness of forging tool material [80,81]. These measurements generate detailed and applicable domain knowledge that reduces uncertainties of existing models to predict local wear effects in the forging tool more reliable.…”

Section: Tool Life Prediction In Hot Forging Determined By Digital Pr...mentioning

confidence: 99%

Perspectives on data-driven models and its potentials in metal forming and blanking technologies

Liewald

Bergs

Groche

et al. 2022

Prod. Eng. Res. Devel.

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Today, design and operation of manufacturing processes heavily rely on the use of models, some analytical, empirical or numerical i.e. finite element simulations. Models do reflect reality as best as their design and structure may appear, but in many cases, they are based on simplifying assumptions and abstractions. Reality in production, i.e. reflected by measures such as forces, deflections, travels, vibrations etc. during the process execution, is tremendously characterised by noise and fluctuations revealing a stochastic nature. In metal forming such kind of impact on produced product today in detail is neither explainable nor supported by the aforementioned models. In industrial manufacturing the game to deal with process data changed completely and engineers learned to value the high significance of information included in such digital signals. It should be acknowledged that process data gained from real process environments in many cases contain plenty of technological information, which may lead to increase efficiency of production, to reduce downtime or to avoid scrap. For this reason, authors started to focus on process data gained from numerous metal forming technologies and sheet metal blanking in order to use them for process design objectives. The supporting idea was found in a potential combination of conventional process design strategies with new models purely based on digital signals captured by sensors, actuators and production equipment in general. To utilise established models combined with process data, the following obstacles have to be addressed: (1) acquired process data is biased by sensor artifacts and often lacks data quality requirements; (2) mathematical models such as neural networks heavily rely on high quantities of training data with good quality and sufficient context, but such quantities often are not available or impossible to gain; (3) data-driven black-box models often lack interpretability of containing results, further opposing difficulties to assess their plausibility and extract new knowledge. In this paper, an insight on usage of available data science methods like feature-engineering and clustering on metal forming and blanking process data is presented. Therefore, the paper is complemented with recent approaches of data-driven models and methods for capturing, revealing and explaining previously invisible process interactions. In addition, authors follow with descriptions about recent findings and current challenges of four practical use cases taken from different domains in metal forming and blanking. Finally, authors present and discuss a structure for data-driven process modelling as an approach to extent existing data-driven models and derive process knowledge from process data objecting a robust metal forming system design. The paper also aims to figure out future demands in research in this challenging field of increasing robustness for such kind of manufacturing processes.

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“…First in this study, a symmetrical 3D FE model of the friction drilling experiments was generated with the software Simufact Forming 16.0. Such 3D FE simulations are commonly used to model forming processes due to their accurate representation of reality [23]. With the high reality fidelity, the computation time increased massively.…”

Section: Numerical Modelling Of Friction Drillingmentioning

confidence: 99%

Finite Element and Finite Volume Modelling of Friction Drilling HSLA Steel under Experimental Comparison

et al. 2021

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Friction drilling is a widely used process to produce bushings in sheet materials, which are processed further by thread forming to create a connection port. Previous studies focused on the process parameters and did not pay detailed attention to the material flow of the bushing. In order to describe the material behaviour during a friction drilling process realistically, a detailed material characterisation was carried out. Temperature, strain rate, and rolling direction dependent tensile tests were performed. The results were used to parametrise the Johnson–Cook hardening and failure model. With the material data, numerical models of the friction drilling were created using the finite element method in 3D as well as 2D, and the finite volume method in 3D. Furthermore, friction drilling tests were carried out and analysed. The experimental results were compared with the numerical findings to evaluate which modelling method could describe the friction drilling process best. Highest imaging quality to reality was shown by the finite volume method in comparison to the experiments regarding the material flow and the geometry of the bushing.

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Multi-Layer Wear and Tool Life Calculation for Forging Applications Considering Dynamical Hardness Modeling and Nitrided Layer Degradation

Cited by 8 publications

References 24 publications

Advanced Complex Analysis of the Thermal Softening of Nitrided Layers in Tools during Hot Die Forging

Advanced Complex Analysis of the Thermal Softening of Nitrided Layers in Tools during Hot Die Forging

Perspectives on data-driven models and its potentials in metal forming and blanking technologies

Finite Element and Finite Volume Modelling of Friction Drilling HSLA Steel under Experimental Comparison

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