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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.

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 and powder metallurgy are briefly discussed. The range of applications of finite elements on the subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE 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 the last five years, and more than 1100 references are listed.

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.

This paper seeks to review the industrial applications of state‐of‐the‐art additive manufacturing (AM) techniques in metal casting technology. An extensive survey of concepts, techniques, approaches and suitability of various commercialised rapid casting (RC) solutions with traditional casting methods is presented.

The tooling required for producing metal casting such as fabrication of patterns, cores and moulds with RC directly by using different approaches are presented and evaluated. Relevant case studies and examples explaining the suitability and problems of using RC solutions by various manufacturers and researchers are also presented.

Latest research to optimize the current RC solutions, and new inventions in processing techniques and materials in RC performed by researchers worldwide are also discussed. The discussion regarding the benefits of RC solutions to foundrymen, and challenges to produce accurate and cost‐effective RC amongst AM manufacturers concludes this paper.

The research related to this survey is limited to the applicability of RC solutions to sand casting and investment casting processes. There is practically no implication in industrial application of RC technology.

This review presents the information regarding potential AM application – RC, which facilitates the fabrication of patterns, cores and moulds directly using the computer‐aided design data. The information available in this paper serves the purpose of researchers and academicians to explore the new options in the field of RC and especially users, manufacturers and service industries to produce casting in relatively much shorter time and at low cost and even to cast complex design components which otherwise was impossible by using traditional casting processes and CNC technology.

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.

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.

Rapid tooling (RT) integrated with additive manufacturing technologies have been implemented in various sectors of the RT industry in recent years with various kinds of prototype applications, especially in the development of new products. The purpose of this study is to analyze the current application trends of RT techniques in producing hybrid mold inserts.

The direct and indirect RT techniques discussed in this paper are aimed at developing a hybrid mold insert using metal epoxy composite (MEC) in increasing the speed of tooling development and performance. An extensive review of the suitable development approach of hybrid mold inserts, material preparation and filler effect on physical and mechanical properties has been conducted.

Latest research studies indicate that it is possible to develop a hybrid material through the combination of different shapes/sizes of filler particles and it is expected to improve the compressive strength, thermal conductivity and consequently increasing the hybrid mold performance (cooling time and a number of molding cycles).

The number of research studies on RT for hybrid mold inserts is still lacking as compared to research studies on conventional manufacturing technology. One of the significant limitations is on the ways to improve physical and mechanical properties due to the limited type, size and shape of materials that are currently available.

This review presents the related information and highlights the current gaps related to this field of study. In addition, it appraises the new formulation of MEC materials for the hybrid mold inserts in injection molding application and RT for non-metal products.

The purpose of this paper is to investigate experimentally the effect of volume of casting, pouring temperature of different materials and shell mould wall thickness on the surface roughness of the castings obtained by using ZCast direct metal casting process.

Taguchi's design of experiment approach was used for this investigation. An L9 orthogonal array (OA) of Taguchi design which involves nine experiments for three factors with three levels was used. Analysis of variance (ANOVA) was then performed on S/N (signal‐to‐noise) ratios to determine the statistical significance and contribution of each factor on the surface roughness of the castings. The castings were obtained using the shell moulds fabricated with the ZCast process and the surface roughness of castings was measured by using the surface roughness tester.

Taguchi's analysis results showed that pouring temperature of materials was the most significant factor in deciding the surface roughness of the castings and the shell mould wall thickness was the next most significant factor, whereas volume of casting was found insignificant. Confirmation test was also carried out using the optimal values of factor levels to confirm the effectiveness of this approach. The predicted optimal value of surface roughness of castings produced by ZCast process was 6.47 microns.

The paper presents experimentally investigated data regarding the influence of various control factors on the surface roughness of castings produced by using ZCast process. The data may help to enhance the application of ZCast process in traditional foundry practice.

This research establishes a suitable casting model for magnesium alloy wheel. The casting of the wheel is an element that must be considered in the design of the wheel. Casting is an important basic process and technology in the field of machinery which is widely used in production, transportation, national defense, social life and other aspects. Computer numerical simulation of the casting process can shorten the product manufacturing cycle, reduce product costs, reduce casting defects and ensure product quality. The casting material in this study is AZ91 magnesium alloy used for wheel lightweight.

Lightweight research of automobile is a significant trend, and people are paying attention to the lightweight design of automobiles. Higher requirement was proposed on design and casting performance of the wheel which is an important part of lightweighting vehicle. In order to achieve better quality, the parametric studies of alloy wheel and casting are necessary. This research designs a new model of automobile wheel, to ensure energy efficiency, the wheels must be as lightweight as possible, using magnesium alloy material for lightweight.

Analysis of casting process is a very complex issue. This research based on finite element theory and actual production, designed reasonable casting model, instant filling and solidification data were obtained. Aiming at reducing casting defects, process improvement of casting riser structure was designed. On the basis of the foundation, it has important guiding significance for actual foundry production.

This research establish a suitable casting model for magnesium alloy wheel. Aiming at reducing casting defects, process improvement of casting riser structure were designed.

Metal casting industry is in recovery phase after the crisis in 2008; customer demand continues to increase, with 98.6 million metric tons cast in 2011. Traditional ferrous and non-ferrous casting techniques require one shot or permanent moulds which require tooling to produce. Tooling particularly for developmental projects can be costly and take valuable time to produce. Additive manufacturing (AM) has been used to manufacture sand patterns for metal sand casting using laser sintering and sand bonding. This research aims to focus on characterising the sand-bonded process developed by ExOne GmbhH Germany.

The approach taken in this research is to evaluate characteristics of parts built in the build volume for dimensional accuracy, tensile and compressive crush strength, density, impact strength and high temperature resistance. These properties are required to compare the 3D sand printing (3DSP) process to direct laser sand sintering (DLSS) and traditional Furan-based casting sand mixtures. The samples were taken from a production machine over a period of 30 days to ensure consistency.

The 3DSP process has the capability to manufacture sand patterns to an accuracy of ±0.5 mm or error less than 0.3 per cent; it has also demonstrated the best build position to achieve accurate parts. The research has demonstrated the 3DSP patterns are comparable to traditional methods for important casting material characteristics such as tensile, compression and impact strength. It has been shown that the 3DSP process is capable manufacturing significantly larger parts, with build production rates up to 30 times higher compared to similar parts manufactured via the DLSS process.

As they has been very few 3DSP machines sold in Europe and particular UK, they has been little research into this new technique, and, therefore, they is a reliance on machine manufactures data for assessment. This research into 3DSP has increased the knowledge of this process significantly.

This research would be of interest to designers and manufacturing engineers wishing to take advantage of the implications of having new design freedom, tool less manufacturing with short lead times in a wide range of materials using fundamentally tried and tested century’s old casting techniques.

The research for this paper revealed very little published academic research in this area; therefore, this work will increase the body of knowledge for this niche AM process.