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This article describes a study that has been made on the automation of deburring in a foundry. Circular castings weighing up to 20kg are deburred before delivery in order to make them fit into machining cells. The maximum production rate of the cylindrical castings on the foundry line is one casting every ten seconds. However, the castings are produced in small batches, typically ranging from 100 to 1,000. After casting and integrated sand blasting and cooling chambers, the castings are transferred further on a conveyor belt. Deburring is today done manually by lifting and pressing against different grinding and deburring machines. Bins and forklifts are used in transport and storage of castings, from production line to deburring and shipment.

Different technologies may currently be used to produce dental prostheses, such as additive manufacturing and traditional milling. This study aims to evaluate and improve the fabrication process for hot-pressed porcelain dental prostheses and compare the use of masked stereolithography apparatus (MSLA) casting to computer-aided design/computer-aided manufacturing (CAD/CAM) casting. The cost-benefit analysis of producing dental prostheses through various technologies, including additive manufacturing and traditional milling, has not been fully explored. The cost of materials and processes used to produce prostheses varies based on complexity of design and materials used, and long-term effects, such as durability and wear and tear, must be taken into account.

Using key elements of part costs and estimation cost models, a multivariable approach was used to evaluate the practicality of the recommended strategy and process improvement.

The research found that MSLA casting provides a higher return on investment than CAD/CAM casting, and the optimized production process could be more suitable for the size and annual demand for prostheses.

Overall, this study highlights the need for a more comprehensive understanding of the cost-benefit analysis of different dental prosthesis production methods and emphasises the importance of evaluating long-term effects on the cost-benefit analysis.

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 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.

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.

High pressure die casting is a widely used industrial process to manufacture complex-shaped products in light alloys. Virtual prototyping techniques, especially numeric-based simulations of the casting process, allow the die filling process to be evaluated and help faster optimization of the gating system, which is the most critical element of the mould. The purpose of this paper is to present a four step approach to design optimal moulds taking advantage of the simulation tools.

No formalized method to design an optimal gating system is available yet and the majority of the studies aim to optimize existing geometries or to choose from alternative solutions. Rather than optimizing the geometries of predefined designs by running attempt trials, the proposed approach defines a procedure to position cavities, gating systems and, finally, to determine the whole mould geometry.

The approach is demonstrated through three different industrial applications. The design of a six-cavity mould for gas cooking burners is reported at first. Then, two test cases, a cup and a radiator, are reported for showing different arrangements of the gating system. The reached quality of the mould design has been assessed using metallographic analyses of the casts.

The design of a mould is strictly correlated to its product and mainly based on a trial-and-error approach. Numerical simulations offer a powerful and not expensive way to study the effectiveness of different die designs and filling processes. The paper proposes a structured approach for the definition of the gating system. It ultimately leads to improvements in both product quality and process productivity, including more effective control of the die filling and die thermal performance.

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.

The Tooling and Casting subgroup of the European Action on Rapid Prototyping (EARP) has undertaken a project to investigate the problems associated with using rapid prototype models as sacrificial patterns for investment casting. The accuracy and surface finish of the models and the castings were also assessed so that a comparison could be made. Models from each process were manufactured by different members of EARP and then three foundries were each given a set of models to convert to castings. Observes that one of the oldest metal manufacturing techniques, which dates back to 4000‐6000 BC, is being used with one of the most modern ‐ rapid 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.

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.