Search results

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

The purpose of this article is to numerically investigate the effect of casting speed on the fluid flow, solidification and inclusion motion under the influence of electromagnetic stirring (EMS) in the bloom caster mold with bifurcated submerged entry nozzle (SEN).

The electromagnetic field obtained by solving Maxwell’s equation is coupled with the fluid flow, solidification and discrete phase model using the in-house user-defined functions. An enthalpy porosity approach and Lagrangian approach are applied for the solidification analysis and non-metallic inclusions motion tracking, respectively.

Investigation shows that the casting speed and EMS significantly affect the steel flow, solidification and inclusion behavior inside the mold. Investigations are being conducted into the complex interplay between the induced flow and the SEN’s inertial impinging jet. In low and medium casting speeds, the application of EMS significantly increases the inclusion removal rate. Inclusion removal is studied for its different size and density and further effect of EMS is also reported on cluster formation and distribution of inclusion in the domain.

The model may be used to optimize the process parameter (casting speed and EMS) to improve the casting quality of steel by removing the impurities.

The effect of casting speed on the solidification and inclusion behavior under the influence of time-varying EMS in bloom caster mold with bifurcated nozzle has not been investigated yet. The findings may assist the steelmakers in improving the casting quality.

The purpose of this paper is to describe how a 3D/1D transient heat transfer model has been developed for getting accurate thermal boundary conditions when investigating the heat transfer in the TiAl castings and also for reducing the computational cost and simplifying the mesh generation.

Heat transfer in the mould is assumed to take place only in a direction perpendicular to the mould wall, called 1D heat transfer. The coordinates of cell centre and the temperature in the mould wall can be calculated by the model instead of meshing mould. Heat transfer in the mould is computed via the FD solution of a 1D heat transfer equation.

For some types of geometry, the model works very well. However, for some, which contain the geometric feature called “dead corner”, the model can't cover. There is some impact on the accuracy of the model.

In the casting industry, the geometry of the casting is usually very complex and contains different features. This leads to difficult meshing when using numerical model to predict the casting process. Furthermore, an accurate calculation is very important on the thermal boundary during filling and solidification, to support practice, to improve the process and minimise the casting defects.

In this paper, a novel method is developed to calculate the heat transfer through the casting‐mould interface to the mould wall in a casting.

The purpose of present paper is to enlarge the knowledge about the performance of gypsum powder to realize complex molds or cores for aluminum casting.

The research was divided into two activities: simple; and complex-part production capability. In the simple-part step, the performance of gypsum powder and the minimum mold thickness that would withstand the casting process. In the complex-part step, the authors first investigated the powder removability as a function of geometry complexity and then binder jetting performance was evaluated for the case of lattice-structure fabrication.

All the geometries tested withstand the casting process demonstrating the benefits in terms of complexity part design; however, the process suffers of all the typical defect of casting as misrun, porosity and cold shut.

The results found in this research improve the benefits related to additive manufacturing application in industrial environment and in particular to the binder jetting technology and the rapid casting approach.

The purpose of this paper is to analyze the current state of the art manufacturing techniques using sand molds for the casting industry by the means of additive manufacturing (AM). In particular, this review will cover two families of 3D printing in regards to sand mold fabrication.

This paper will discuss the sand casting manufacturing processes of AM by binder jetting (3D printing) and selective laser sintering. Scientific articles, patents and case studies are analyzed. Topics ranging from the technology types to the economic implications are covered.

The review investigates new factors and methods for mold design, looking at mechanical properties and cost analysis as influenced by material selection, thermal characteristics, topological optimization and manufacturing procedure. Findings in this study suggest that this topic lacks vigorous scientific research and that the case studies by manufacturers thus far are not useful.

As demonstrated by the limited data from previous published studies, a more comprehensive and conclusive analysis is needed due to the lack of interest and resources regarding the AM of sand molds.

This study is a useful tool for any researchers with an interest in the field of AM of sand molds.

Key perspectives are proposed.

This review highlights current gaps in this field. The review goes beyond the scientific articles by curating patents and professional case studies.

This paper aims to investigate the current state, technological challenges, economic opportunities and future directions in the growing “indirect” hybrid manufacturing ecosystem, which integrates traditional metal casting with the production of tooling via additive manufacturing (AM) process including three-dimensional sand printing (3DSP) and printed wax patterns.

A survey was conducted among 100 participants from foundries and AM service providers across the USA to understand the current adoption of AM in metal casting as a function of engineering specifications, production demand, volume and cost metrics. In addition, current technological and logistical challenges that are encountered by the foundries are identified to gather insight into the future direction of this evolving supply chain.

One of the major findings from this study is that hard tooling costs (i.e. patterns/core boxes) are the greatest challenge in low volume production for foundries. Hence, AM and 3DSP offer the greatest cost-benefit for these low volume production runs as it does not require the need for hard tooling to produce much higher profit premium castings. It is evident that there are major opportunities for the casting supply chain to benefit from an advanced digital ecosystem that seamlessly integrates AM and 3DSP into foundry operations. The critical challenges for adoption of 3DSP in current foundry operations are categorized into as follows: capital cost of the equipment, which cannot be justified due to limited demand for 3DSP molds/cores by casting buyers, transportation of 3DSP molds and cores, access to 3DSP, limited knowledge of 3DSP, limitations in current design tools to integrate 3DSP design principles and long lead times to acquire 3DSP molds/cores.

Based on the findings of this study, indirect hybrid metal AM supply chains, i.e. 3DSP metal casting supply chains is proposed, as 3DSP replaces traditional mold-making in the sand casting process flow, no/limited additional costs and resources would be required for qualification and certification of the cast parts made from three-dimensional printed sand molds. Access to 3DSP resources can be addressed by establishing a robust 3DSP metal casting supply chain, which will also enable existing foundries to rapidly acquire new 3DSP-related knowledge.

This original survey from 100 small and medium enterprises including foundries and AM service providers suggests that establishing 3DSP hubs around original equipment manufacturers as a shared resource to produce molds and cores would be beneficial. This provides traditional foundries means to continue mass production of castings using existing hard tooling while integrating 3DSP for new complex low volume parts, replacement parts, legacy parts and prototyping.

Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.

A systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.

This study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.

This paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.

The systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.

Foundry produces cast metal components and parts for various industries and drives manufacturing excellence all over the world. Assuring quality of these components and parts is vital for the end product quality. The complexity in foundry operations increases with the complexity in designs, patterns and geometry and the quality parameters of the casting processes need to be monitored, evaluated and controlled to achieve expected quality levels.

The literature addresses quality improvement in foundry industry primarily focusing on surface roughness, mechanical properties, dimensional accuracy and defects in the cast parts and components which are often affected by numerous process variables. Primary data are collected from the experts working in sand and investment casting processes. The authors perform machine learning analysis of the data to model the quality parameters with appropriate process variables. Further, cluster analysis using k-means clustering method is performed to develop clusters of correlated process variables for sand and investment casting processes.

The authors identified primary process variables determining each quality parameter using machine learning approach. Quality parameters such as surface roughness, defects, mechanical properties and dimensional accuracy are represented by the identified sand-casting process variables accurately up to 83%, 83%, 100% and 83% and are represented by the identified investment-casting process variables accurately up to 100%, 67%, 67% and 100% respectively. Moreover, the prioritization of process variables in influencing the quality parameters is established which further helps the practitioners to monitor and control them within acceptable levels. Further the clusters of process variables help in analyzing their combined effect on quality parameters of casting products.

This study identified potential process variables and collected data from experts, researchers and practitioners on the effect of these on the quality aspects of cast products. While most of the previous studies focus on a very limited process variables for enhancing the quality characteristics of cast parts and components, this study represents each quality parameter as the function of influencing process variables which will enable the quality managers in Indian foundries to maintain capability and stability of casting processes. The models hence developed for both sand and investment casting for each quality parameter are validated with real life applications. Such studies are scarcely reported in the literature.

The purpose of this paper is to develop a novel process of integral ceramic molds for investment casting of hollow turbine blades.

At first, a resin pattern of a hollow turbine blade prototype is fabricated by stereolithography (SL). And then aqueous gelcasting process is utilized to fill the resin pattern with ceramic slurry of low viscosity and low shrinkage, through in situ polymerization of the slurry a ceramic mold is formed. At last, the ceramic mold for investment casting of hollow turbine blade is obtained by vacuum drying, pyrolyzing and sintering.

An integral ceramic mold is successfully fabricated by combining SL and gelcasting process, cores and shell are connected with each other and thus high relative position accuracy is guaranteed. Properties of integral ceramic mold at room temperature and high temperature satisfy the requirements of directional casting for complex‐shaped thin‐walled blades.

Because the integral ceramic mold is a close body, it is very difficult to directly measure its inner dimensions and the relative position accuracy of cores and shell, and the further research is needed.

This method enhanced the versatility of using SL prototype in the fabrication of integral ceramic mold for investment castings. Although this paper took a hollow turbine blade as an example, this method is also capable of fabricating integral ceramic molds for other complex investment castings.

The main purpose of this paper is to calculate the analytical solution or a closed-form solution for the temperature distribution in the heterogeneous casting-mould system.

First, the authors formulate and analyze the mathematical formulation of heat conduction equation in the heterogeneous casting-mould system, with an arbitrary assumption of the ideal contact at the cast-mould contact point. Then, He-Laplace method, based on variational iteration method (VIM), Laplace transform and homotopy perturbation method (HPM), is used to elaborate the analytical solution of this system. The main focus of He-Laplace method is to find the Lagrange multiplier with an easy approach which enables the implementation of HPM very smoothly and provides the series solution very close to the exact solution.

An example is considered to show that He-Laplace method provides the efficient results for calculating the temperature distribution in the casting-mould heterogeneous system. Graphical representation and error distribution represents that He-Laplace method is very simple to implement and effective for casting-mould heterogeneous system.

The work in this paper is original and advanced. Specially, calculation of Lagrange multiplier for casting-mould system has not been reported in the literature for this work.