This study presents the results of an investigation that characterises the thermophysical properties of an investment casting mould, comprising of a Zirconium dioxide/Cobalt aluminate prime slurry and a fused Silica/fibre reinforced backup slurry. Growing prevalence of successful computer simulations within the foundry industry enables defects that emerge during the casting process to become increasingly predictable, providing cost-effective alternatives to trial castings. The viability of these simulations as predictors is heavily dependent upon the facilitation of accurate material property data, as attained through this investigation. Differential scanning calorimetry (DSC) and laser flash analysis (LFA) were utilized to determine the specific heat capacity and thermal diffusivity, respectively. These values, in combination with the material density and linear coefficient of thermal expansion, have been used to determine the thermal conductivity of the mould. With the aim of verifying these parameters, initial studies in Flow-3D® simulation software have been performed to determine the constraints needed to reduce variability in simulation parameters. Due to the diversity of casting moulds used throughout the industry, ensuring the material database is kept as comprehensively populated as possible is a crucial undertaking. 

Uncertain and imprecise data are inherent to many domains, e.g. casting lightweight components. Fuzzy logic offers a way to handle such data, which makes it possible to create predictive models even with small and imprecise data sets. Modelling of cast components under fatigue load leads to understanding of material behaviour on component level. Such understanding is important for the design for minimum warranty risk and maximum weight reduction of lightweight cast components. This paper contributes with a fuzzy logic-based approach to model fatigue-related mechanical properties of as-cast components, which has not been fully addressed by the current research. Two fuzzy logic models are constructed to map yield strength to the chemical composition and the rate of solidification of castings for two A356 alloys. Artificial neural networks are created for the same data sets and then compared to the fuzzy logic approach. The comparison shows that although the neural networks yield similar prediction accuracy, they are less suitable for the domain because they are opaque models. The prediction errors exhibited by the fuzzy logic models are 3.53% for the model and 3.19% for the second, which is the same error level as reported in related work. An examination of prediction errors indicated that these are affected by parameters of the membership functions of the fuzzy logic model.

Aluminum alloys are today entirely recyclable and are seen as a sustainable material. However, there are limitations in the use of aluminum from material strength and cost perspective. Nickel, copper and rare earth metals are alloying elements that may provide strength at room and elevated temperatures. These are, however, often seen as harmful from a sustainability viewpoint. Additionally, these alloying elements are commonly costly. The current paper makes an analysis of the sustainability-strength dimension of alloying, together with a cost perspective, to guide alloy producers and alloy users in making an educated choice of direction for future materials and material development.

This paper aims to investigate the anodising behaviour of Al-Si components produced by rheocasting, to understand the effect of the surface liquid segregation (SLS) on the anodising response. The material investigated was EN AC 42000 Al-alloy with an addition of 150 ppm Sr. The component was rheocast and conventionally liquid cast for benchmarking. The RheoMetalTM process was used to prepare slurry and subsequently cast using a vertical pressure die casting machine. Prior to anodising, mechanical grinding was used as pre-treatment method for selected samples as comparison with components in the as-cast state. Anodising was performed on the components using a constant controlled voltage at 25 V, in 1 M H2SO4, at room temperature. The duration of anodising was varied from 30 mins to 120 mins to examine the relationship between oxide layer thickness and the anodising time. The oxide layer was investigated and characterised. The results demonstrated that the presence of the SLS layer, which was enriched with alloying elements, had a significant influence on the anodising behaviour of the cast component. The oxide layer thickness of the components produced by rheocasting and fully liquid casting was measured and compared. The relations between the oxide layer thickness and anodising time, as well as the casting methods are presented and discussed in this paper.

When manufacturing tooling inserts for HPDC (High Pressure Die Casting), several manufacturing steps such as milling, heat treatment, electro discharge machining and finally surface treatment are involved. By instead manufacturing the insert by SLM (Selective laser melting), the process is expected to be quicker and with less material waste compared to the traditional manufacturing. Examples of other expected advantages is higher product variant flexibility and the possibility of making conform cooling channels, extending the die life. However, the insert is part of a die system involving many components. The insert cannot be designed and manufactured without considering the complete die system. This paper seeks how to integrate the insert design in the die assembly design. This is done via an example component and in cooperation with die manufacturing firms. The result is that the printing is a minor step of the total manufacturing process and that special design considerations needs to be taken for an SLM insert. New die concepts are needed that will minimise the amount of material, reduce the tolerance and surface demand and support the subdivision of the die into several printed parts.

The influence of cooling rate on the formation of iron-rich intermetallic phases during solidification of unmodified and strontium-modified Al-7Si-0.3Mg alloys has been investigated. The effect of strontium on the intermetallic phases was evaluated in unquenched and quenched samples. Samples were quenched before the start of the Al-Si eutectic reaction, along the Al-Si eutectic reaction and just after the end of solidification. The results show that the addition of strontium increased the size of both β-Al5FeSi and π-Al8FeMg3Si6 at low cooling rates. For unmodified and strontium-modified alloys, an increase of cooling rate resulted in a decrease in size of the intermetallic phases, particularly in the strontium modified alloy. In the strontium modified alloy quenched before the start of the Al-Si eutectic reaction, π-Al8FeMg3Si6 appeared as thin platelets at the eutectic cell boundaries. Chinese script-like π-Al8FeMg3Si6 and platelet-like β-Al5FeSi intermetallic phases were observed uniformly distributed in the eutectic regions in the unmodified alloy quenched before the start of the eutectic reaction. Strontium modified semi-solid Al-7Si-0.3Mg castings were produced and the type of intermetallic phase, morphology, size, area fraction and distribution were similar to that observed in the strontium modified alloy quenched before the start of the Al-Si eutectic reaction.

Digitalization of manufacturing requires building models to represent accumulated data and knowledge on the products and processes. The use of formal knowledge models allows for increase of the automation level leading to more sustainable manufacturing. Casting is important for different industries because it offers a great freedom of designing for weight reduction. This paper presents an approach to modelling of cast component properties that is based on fuzzy logic. The approach includes learning of the fuzzy inference rules from the data. The constructed fuzzy logic models can be used to tune the manufacturing process to produces cast components with desired properties. The evaluation of the results demonstrates that the accuracy of the two created models are 3.58% and 3.15% respectively with the learned fuzzy inference rules being identical to the manually created ones. The presented approach can help to automate the management of cast component manufacturing. 

This study investigates the scratch load effect, from 100 to 2000 mN, on micro-mechanisms involved during scratching. A pearlitic and three ferritic Compacted Graphite Irons (CGI) solution strengthened through addition of 3.66, 4.09, and 4.59 Si wt% were investigated. Good correlation was observed between hardness measurements, tensile testing, and scratch results explaining the influence of matrix characteristics on scratch behaviour for investigated alloys. A significant matrix deformation, change in frictional force and scratch coefficient of friction was observed by increase in scratch load. In all cases, microscratch depth and width increased significantly with load increasing, however pearlitic CGI showed most profound deformation, while the maximum and minimum scratch resistances were observed for high-Si ferritic and pearlitic CGI alloys, respectively.

The mechanical properties of Al-Si alloys are affected by several microstructural features such as secondary dendrite arm spacing (SDAS), size and shape of eutectic Si-particles, presence of intermetallics as well as by porosity. In the current study, Al-Si-Cu alloy A380 was prepared by a unique directional solidification method to produce samples with two different SDAS of 9 μm and 27 μm. The lower solidification rate resulted in larger SDAS, larger grain size, larger eutectic Si and larger intermetallics including Fe-rich β phase. The microstructure with higher solidification rate was found to be finer and more homogeneous with smaller eutectic Si and intermetallics. The specimen with larger SDAS exhibited stronger texture than the one with smaller SDAS. The specimen with smaller SDAS showed improved mechanical properties including YS, UTS and ductility.