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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 identify the influencing factors which cause casting defects and determination of optimum value of factors to minimize these defects in a melt shop industry, situated in north India. Percentage contribution of these factors is also estimated to develop an empirical expression between process performance and independent input variables.

Optimization technique for melt shop process parameters of a cast iron differential housing cover based on the Taguchi method is proposed. The focus of this paper is on the robustness of the sand casting process and the case study is based upon a leading automobile foundry industry, located in north India. Taguchi's experimental design and regression analysis techniques are used to optimize the control factors, resulting in improvement of the product quality and stability. The various confirmation tests are also carried out in the range of process parameters.

The outcome of this case study is to optimize the process parameters of the melt shop process, which leads to minimizing the casting defects. The process parameters considered are: mild steel, pig iron, cast iron, ferrosilicon, lime stone, ferromanganese, cock and ferrochrome. Best proportions of charge constituents that are contributing to casting defects in melt shop are identified in the first stage. These identified factors are analyzed using “Design of Experiments” approach in the second stage. ANOVA analysis is also performed for robust design of factor values and an appropriate empirical model is formulated.

A lot of effort has been put into developing the appropriate empirical model for the automobile foundry industry but additional work may also be done for gating design of the casting industry.

The paper shows that the process parameters of any casting industry can be optimized and casting defects in the melt shop can be identified in the first stage.

The research findings could be applied to various manufacturing industries, especially the casting industries.

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.

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.

The purpose of this research was to develop new sustainability indicators consistent with the sand mould casting industry, through benchmarking of cleaner production (CP), in order to identify the levels of practice and performance of companies of the casting sector. In addition, a lean manufacturing checklist was specified in order to verify the presence of lean manufacturing techniques employed to eliminate waste towards CP. No previous work was found in the literature that attempts to assess practices and performance of companies performing sand mould casting (a significantly polluting manufacturing process) in the context of CP and lean manufacturing.

For the application of this benchmarking, nine companies from the sand mould casting sector were studied, where the profile of each company was analysed through eight variables and 47 indicators. Data was obtained through face-to-face visits and questionnaire application in the companies, and the data was analysed both quantitatively and qualitatively.

The results obtained were the diagnosis of companies' practices and performance resulting from their position in the benchmarking charts, as well as the identification of the areas in which companies should implement improvements aiming at achieving CP.

This research was developed specifically for sand mould casting companies, and each process has its own characteristics

14 companies were invited to participate in this survey, but nine companies agreed to participate. Unfortunately, there were companies that declined to participate in the survey.

It is important to diagnose casting companies regarding CP practices, performance and deployment potential. Thus, important negative issues in the company can be identified, and with this information, they can develop actions focussed on cases that need more attention. In addition, this work contributes to evaluate the relationship and efficiency of improvement actions developed by companies in the context of both lean manufacturing and CP, aiming to reduce or eliminate the environmental impact. The improvement of practices and performance of a company regarding CP is considered to be beneficial to supply chain management in the context of sustainability, as the other participating companies are likely to seek ways to reduce environmental impact, and the diagnostics provided by this work may also be used by those companies.

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 explore Six Sigma practices in a casting industry, that could improve the green sand casting process in a foundry by reducing the casting defects. The goal was to determine which variables influenced this evolution and the relative weight of critical success factors as the methodology developed.

The DMAIC (Define, Measurement, Analyze, Improve, and Control)‐based Six Sigma approach is implemented to improve the green sand casting process and has made the process more robust to quality variations. Analysis of various critical process parameters of the melt shop is also carried out with the help of Taguchi's method of experimental design.

The proposed techniques optimized control factors, resulting in superior quality and stability of the green sand castings process, which contributes to minimizing the casting defects and improving the Sigma level of the industry.

This study was carried out with some boundaries such as the number of castings of differential housings, available resources, time constraints, etc.

This paper is most valuable for the foundry industry, which can avail the direct benefit of Six Sigma results from the reduction in the number of defects due to improved casting processes and dispels the myths concerning the hardly ever use of Six Sigma in the casting industry.

The novelty of the paper lies in conducting a comparative study on the performance of a Six Sigma project. The paper will be valuable for quality professionals and management personnel in the casting industry.

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 quality of production is an essential factor for the performance measure of a system; a casting process is the same section. It is a type of metal-forming practice in which the required shape of metal is acquired by pouring molten metal into the mold cavity and allowing it to solidify. Casting is done to provide strength and rigidity to the parts of a system for bearing mechanical impacts. The purpose of this paper is to investigate the various aspects which affect the casting process in the foundry industry, in order to optimize the quality of casting, with the assumption that sufficient repair facility is always available.

The considered casting system can have many defects such as the mold shift defect, blowhole defect, defect of shrinkage and porosity, defect of inclusion, defect of cold shut and much more. The studied system can be in three states during the process, namely, good state, failed state and degraded state. The system can repair after minor failures as well as a major failure. The average failure rates of various defects of the system considered as constant and repairs follow the general time distribution. The system is analyzed with the help of the supplementary variable technique and the Laplace transformation for evaluating its various performance measures in order to improve its performance/production.

This work provides a strong understanding of the casting industry, that which failure affects the production of casting and how much. For better understanding, the results have been demonstrated with the help of graphs.

In the present paper, a mathematical model based on the casting process in manufacturing industry has been developed.

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.