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1.
Baitiang, Chinnadit1; Krüger, Mathias2; Piesker, Sven2; H. Williams-Boock, Bernd2; Weiß, Konrad1; Volk, Wolfram3
1RWP. Gesellschaft beratender Ingenieure für Berechnung und rechnergestützte Simulation m.b.H., Germany
2Ortrander Eisenhütte GmbH, Germany
3Chair of Metal Forming and Casting, Technical University of Munich, Germany
PREDICTION OF MECHANICAL PROPERTIES OF CAST IRON PART AND ANALYSIS OF CASTING DEFECTS USING PRODUCTION DATA FROM AN AUTOMATIC SAND MOULDING FOUNDRY
Abstract
Scrap reduction is one of the most important goals for foundries, leading to higher profit. However, for most foundries scrap parts can only be detected at the end of the production line, which is after hours too late to correct the process. It would be desirable for foundries, if cast part properties and quality can be forecasted based on inline process data, to allow earlier scrap detection and process correction. For this, we introduced innovative methods to predict the quality and properties of cast iron parts and find out the scrap causes based on production data (without part-specific traceability) from a foundry with an automatic sand moulding process (Disamatic). Firstly, geometry-specific models for the prediction of mechanical properties (hardness and tensile strength) based on the chemical composition of the melt were created. Two different modeling methods, multiple linear regression (MLR) and artificial neural network (ANN) were used. The models were evaluated by comparing measured and predicted data through charts and mean absolute error. Secondly, scrap relevant parameters and their proper working boundaries were determined using a comparative study of inline parameters between good and scrap production batches. As a result, both MLR- and ANN models show good prediction performance in predicting hardness (slightly better for the MLR). Unstable recycled sand moisture and temperature, clay- and water contents of moulding material were found to be the reasons for most scrap. Proper working boundaries for these parameters were determined by observing parameter values from good production batches. With our models and boundaries, the foundry can predict part properties and detect possible scrap at least one hour in advance by observing inline parameters. This contributes to scrap reduction and thus more cost savings for the foundry.
Keywords: Cast iron; Disamatic; Mechanical properties; Multiple linear regression; Artificial neural network; Casting defects
2.
Zovko Brodarac1 , A. Mahmutović2 , S. Zeljko3 , L. Zeljko1
1University of Zagreb Faculty of Metallurgy (HR)
2TC Livarstvo Ltd, (SI)
3Plamen Ltd (HR)
NUMERICAL SIMULATION IN OPTIMIZATION OF THIN-WALLED EN-GJL-200 CASTING
Abstract
Implementation of new strategies and concepts such as “Near net shape castings” and “Right for the first time” represents an imperative for nowadays foundry production. High material utilization, with a minimal number of forming operations and defects avoiding, is the main goal for casting producers. Therefore, numerical simulation as a part of CAD/CAE technologies represents an indispensable tool for achieving competitiveness in the global market.
Numerical simulation of casting poring and solidification represents a description of physical phenomena based on a mathematical model. The application of computer numerical simulations, which are based on complex and comprehensive mathematical models such as Fourier law, found its significant application in consideration of thermal processes in the foundry. Numerical simulation enables the analogical display of metallurgical processes by calculation and graphical disposition of the process from the pouring to the final casting solidification. The solidification process is a very complex process that comprehends knowledge related to material and technology behaviour and interactions. The complexity of metal casting consists of element interactions and mass transfer during solidification, and technological development including heat transfer. The most useful numerical method is the finite difference method due to its simplicity, but the finite element method is more accurate and does not have any limitation concerning the complexity of geometric shapes.
The focus of this investigation was the optimization of pouring and solidification process of thin-walled EN-GJL-200 casting using numerical simulation. The complex geometry of thin-walled casting represents the challenge due to crusted parts and stress bending of casting in the existing technological setup. Numerical simulation optimization reveals changes in technological parameters of the gating system, venting system, and support. Optimization enables even filling with castings to prevent an extensive thermal overload and consequently stress of particular parts of castings.
Keywords: numerical simulation, EN-GJL-200, thin-wall casting, solidification
3.
Ferčec1, A. Slana1, A. Šibila1
1TALUM d.d. Kidričevo, Tovarniška cesta 10, 2325 Kidričevo (Sl)
CHARACTERIZATION OF DEFECTS IN ALUMINUM CASTINGS PRODUCED BY TILT GRAVITY CASTING IN RELATION TO PROCESS PARAMETERS
Abstract
In the production process of aluminum castings, we often face defects that are detected when castings have already been assembled or just before final use. These defects include leaks that allow gas or liquid to pass through the walls of castings. Thus, for some castings tightness represents the key feature. Such castings include housings, covers, etc. To achieve a stable production process and to understand the root cause, it is necessary to perform research or characterization of defects with computer tomography, optical microscope, and scanning electron microscopy. In this paper, we performed systematical research of leaking parts cast with tilt gravity casting to determine the cause for the leakage. We wanted to relate the causes of leakage to process parameters affecting defects that lead to leakage. In the study, we found that the main reason for leakage of cast parts cast by tilt gravity casting are inclusions or oxide film and shrinkage porosity. For the formation of shrinkage porosity, we focused on the influence of mold temperature. For the measurement of mold temperature, we used a thermal imaging camera. To determine the impact of mold temperature on the solidification of cast parts we used a casting simulation.
Keywords: tilt gravity casting, casting defects, process parameters
4.
Peter Kirbiš1,2, Ivan Anžel2, Mihael Brunčko1
1SIJ Metal Ravne d.o.o. (SI)
2University of Maribor, Faculty of Mechanical Engineering (SI)
CONTINUOUS CASTING OF HIGH CARBON NANOSTRUCTURED BAINITIC STEEL
Abstract
The current research work describes the solidification and microstructure formation during vertical continuous casting of a high carbon nanostructured bainitic steel (0.7C-5.5Mn-1Cr1.5Al-0.6Mo) in laboratory conditions.
Nanostructured bainitic steels achieve exceptional combinations of mechanical properties due to their very fine microstructure where the bainitic ferrite plate thickness is only about 10 nm. This very fine structure is obtained by bainite formation at very low temperatures below 200 °C and down to ambient level. To ensure such low transformation temperatures and suppress the formation of martensite below room temperature these steels have a high carbon content and are also alloyed with Mn, Cr, Ni, and Mo. Additionally, in order to suppress the precipitation of carbides during bainite formation, they contain high amounts of Si and Al either separately or in combination. Such a complex composition is challenging from the viewpoint of production using continuous casting.
It was observed that the newly developed steel can be successfully continuously cast, provided stable solidification conditions can be maintained during the casting process.
Keywords: Nanostructured bainitic steel, continuous casting, segregations