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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.

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 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.

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.

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.

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.

Optimised concrete components are often of complex geometries, which are difficult and costly to cast using traditional formworks. This paper aims to propose an innovative formwork system for optimised concrete casting, which is eco-friendly, recyclable and economical.

In the proposed formwork system, ice is used as mould pattern to create desired geometry for concrete member, then sand mould is fabricated based on the ice pattern. A mix design and a mixing procedure for the proposed sand mould are developed, and compression tests are also performed to ensure sufficient strength of the sand mould. Furthermore, surface preparation of the sand mould is investigated for easy demoulding and for achieving good concrete surface quality. Additionally, recyclability of the proposed sand mould is tested.

The proposed mix design and mixing procedure can provide sufficient strength for sand mould in concrete casting. The finished components exhibit smooth surfaces and match designed geometries, and the proposed sand mould can be fully recycled with satisfactory strength.

To the best of the authors’ knowledge, this is the first study that combines ice pattern and sand mould to create recyclable formwork system for concrete casting. The new techniques developed in this research has great potential to be applied in the fabrication of large-scale concrete structures with complex geometries.

The general procedure of thermal optimisation in the sand casting process is addressed. Various aspects of design including the size and position of feeders and chills are discussed and practical approaches are presented to search for optimum design configurations. An algorithm is also presented for finding the optimum size, position and number of chills in a sand casting process. The presence of the chill(s) in the casting configuration is simulated using a one‐dimensional heat conduction model and proper inter‐facial heat transfer coefficients. The method is efficient as all computations are carried out on the same grid and there is no need for re‐meshing due to re‐sizing or re‐positioning of the chills. A finite element thermal analysis module is linked to a commercial optimisation tool to search for the optimum set of design variables and a computationally efficient sensitivity analysis method is introduced. Three sand casting test cases are solved to validate and demonstrate the optimisation procedure and these show its use to determine the optimum size, location and number of feeders and chills on a section through a casting.

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 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.