M. Terčelj

Assessment of temperature on the die surface in laboratory hot metal forming

Abstract The temperature in the die surface layer during hot forming is difficult to measure accurately with a thermocouple and is still the subject of experimental and numerical modelling studies. In this paper a method of embedding the thermocouple just below the die surface, the application of such an embedded thermocouple in measurements of the die temperature during cyclic hot compression, and quantitative estimation of the temperature on the die surface is described, based on numerical extrapolation of measured data which were obtained by the use thermocouples embedded in the die. The results show that the applied “thermocouple just below the die surface–numerical extrapolation” method demands a precise knowledge of the distance of the thermocouple from the ideal die surface. The temperature on the die surface can be more easily assessed if it is slightly above the tempering temperature of the die material and if the method of “multiple contact” is applied. It is essential that no wear occurs. Thus, measurements of microhardness values can indicate to what depth of the embedded thermocouple the measured values are related. Exact calibration of the surface temperature demands additional indirect methods.

Suitability of CAE neural networks and FEM for prediction of wear on die radii in hot forging

Abstract Prediction of tool wear in hot die forging along the entire arbor radius by wear models known so far is a very difficult task. On these parts of tools significant changes of contact pressure and sliding lengths occur along the die curvature during the plastic flow of material formed. A new approach presented in the paper combines the use of a conditional average estimator neural network (CAE NN) with the exploitation of results obtained by the finite element method (FEM) and also data from other sources. Consequently new parameters as well as the results of experimental work can be taken into account. In this paper a brief overview of models for prediction of tool (die) wear are discussed. The theoretical background of CAE NN, as well as its application to the modeling of the tool wear phenomenon, is presented. Some results of FEM analysis of the hot forging process that serve as input parameters in the CAE NN model are also briefly discussed. Two relevant practical applications are shown. In the first example, tool wear was modeled at a higher number of strokes (blows), by knowing wear at a lower number of strokes. In the second example, the number of strokes was the output parameter—the number of strokes causing predetermined wear at any point of the tool engraving curvature (arbor radius) was predicted. A comparison between the measured and predicted values of wear demonstrated good agreement that was assessed by a corresponding coefficient of determination.

Response to Hot Deformation Conditions and Microstructure Development of Nimonic 80A Superalloy

Laboratory compression tests at different temperatures and strain rates have been performed on Nimonic 80A superalloy to define optimal hot forming characteristics. A mathematical expression connecting mean grain size and true stress is presented using a Hall–Petch-like equation. The evolution of microstructure at various sample positions in correlation with deformation temperatures, strain, and strain rates has also been investigated. Optimal hot-working conditions are determined using processing maps and obtained microstucture.

Three Important Points that Relate to Improving the Hot Workability of Ledeburitic Tool Steels

In this article, the importance of selecting the right process parameters for ledeburitic tool steels, i.e., casting temperature, cooling rate, and soaking temperature, which is needed to improve their intrinsic hot workability, is presented. The results were obtained from investigations in industrial practice and in the laboratory. It was found that inappropriate selection of these process parameters results in the occurrence of carbides that are not usually present in these types of steels, in terms of type, shape, fractions, and their distribution that decreases the steels’ hot workability. In particular, a casting temperature that is too high and cooling rates that are too low result in the additional precipitation of carbides, which are not common in these steels, leading to cracking, predominately along these carbide stringers and consequently to a deterioration of the hot workability and the properties of the final products. It was also found that by selecting the proper soaking conditions, it is possible to decrease the negative influence of previous processing parameters on the hot workability.

Wear Progress of Nitrided Layer at Low, Medium and High Contact Pressures During a Laboratory Simulation of Aluminium Hot Extrusion

The progress of wear associated with the compound and diffusion layers of nitrided samples was studied by employing laboratory tests at low, medium and high contact pressures, simulating the conditions occurring during the hot extrusion of aluminium. It was found that with increasing of contact pressure also wear rates increase that indicates on predominately frictional removal of compound layer which was confirmed by scanning electron microscopy and back-scattered electron micrographs as well as energy-dispersive spectroscopy analysis of tested surfaces. Testing at medium contact pressures reveals some common features observed at testing at lower as well as at higher contact pressures. The essential difference between the testing at medium and low contact pressures is in the density of the obtained micro-craters and appearance of their extension in sliding direction at medium contact pressures. At higher contact pressure, removal of compound layer is already preferentially oriented in sliding direction in the first stage, while at medium contact pressure, this is observed only in later stages of degradation progress.

Determination of scrap/supply probability curves for the mechanical properties of aluminium alloys in hot extrusion using a neural network-like approach

In this paper a neural network-like approach that accounts for the different uncertainties in the hot extrusion of AA6082 alloys is given. The results, presented in the form of scrap/supply curves, suggest the use of a probabilistic approach in the process of hot extrusion. The proposed approach considers both the epistemic and aleatory uncertainties and takes into account all the available influential input variables. The use of the CAE neural network, which is a special type of probabilistic neural network, is proposed as a powerful tool in the design and partial optimization of the hot-extrusion processes in real, industrial aluminium production. It was found that mechanical properties and the yield can be additionally optimized by reducing the epistemic uncertainties, which consequently requires more accurate measurements and more reliable control of the production processes.

Thermal Fatigue Behavior of High Cr Roller Steel

In this work thermal fatigue resistance of 1.7C, 11.2Cr, 2.0Ni, 1.2Mo steel for hot working rolls was studied using our newly developed test rig with specially prepared test samples. Tests were carried out in temperature range between 500–700 \({^\circ }\)C whereas relevant characteristics related to cracks after 200, 500, 1000, and 2500 cycles were obtained. Average length of all cracks, their density, average length of five longest cracks, and relevant microstructural characteristics of tested specimens were determined. It was found that initiation of cracks is strongly related to the cracking and spalling of carbides at specimens surface layer and that cracks growth is related to the characteristics of carbides. For comparison also results for Indefinite Chilled Double Poured roll cast iron are given. Based on obtained results, possible improvements of thermal fatigue resistance of these two materials are discussed.

Amelioration of surface cracking during hot rolling of AISI D2 tool steel

ABSTRACT Reported is a relationship between a profile edge cracking during hot rolling of AISI D2 tool steel and material and processing parameters. Several months of observation of industrial hot rolling was done for neural network analysis and complemented with equilibrium thermodynamics calculations and laboratory hot deformation tests. Industrial results, in general, show that for the same chemical composition, hot rolling yield decreases with an increased profile aspect ratio. Cr content is significant for the soaking and strongly correlated with a hot workability at upper and lower limits of the hot working temperature range. Laboratory hot compression tests were employed to determine the optimal soaking temperature and to study hot workability to expand safe hot working temperature window.

Influence of cooling mode in relation to casting and extrusion parameters on mechanical properties of AA6082

Abstract In this study, conditional average estimator neural networks (CAE NNs) were used for an analysis of the common influences of the cooling mode in relation to the ram speed, extrusion ratio, casting speed and casting temperature on the yield strength and the elongation of an extruded profile made from aluminium alloy (AA)6082. The obtained results from the analysis revealed very complex relationships between these parameters. In order to maximise the values for the yield strength and the elongation, the values for the ram speed, extrusion ratio, casting speed and casting temperature should be optimised in relation to the mode of cooling.

Testing of thermal fatigue resistance of tools and rolls for hot working

Abstract In the present contribution two tests for thermal fatigue testing, which have been developed in our group, are presented. First test has provided internal cooling system of sample, while second has external cooling. For both tests heating and cooling of samples are computer guided that enables very reliable results of testing. The first test is more appropriate for testing the base material, i.e. roll cast irons, roll steels, tool steels. The second test is more appropriate for experiments that are aimed for selection of appropriate tool surface treatment, i.e. laser cladding, nitriding, coating, etc., and to compare and to achieve improved resistance against thermal fatigue of produced surface layers.