Influence of Mold Material on the Mold Stability for Foundry Use

Sinha, Ν.Κ.; Choudhary, I. N.; Singh, Jayant K.

doi:10.1007/s12633-021-01070-y

Cited by 9 publications

(6 citation statements)

References 26 publications

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“…Analytical modeling of casting quality parameters simulation to determine optimal setting of process variables to attain the required quality level. Literature shows process variability induced by the molds such as from mold material, mold composition, amount of binder, additives and ramming pressure affecting the quality of casting and process characterization (Narasimha Murthy and Babu Rao, 2017;Rao and Murthy, 2018;Sinha et al, 2022). Process variables like sand grain fineness number, amount of clay, moisture content and degree of ramming is also found to significantly affect the mold properties (Xu et al, 2019).…”

Section: Literature Review Methodsmentioning

confidence: 99%

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Analytical modeling of quality parameters in casting process – learning-based approach

Suthar

Persis

Gupta

2022

IJQRM

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PurposeFoundry 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.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueThis 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.

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Section: Literature Review Methodsmentioning

confidence: 99%

“…Literature shows process variability induced by the molds such as from mold material, mold composition, amount of binder, additives and ramming pressure affecting the quality of casting and process characterization (Narasimha Murthy and Babu Rao, 2017; Rao and Murthy, 2018; Sinha et al. , 2022).…”

Section: Literature Backgroundmentioning

confidence: 99%

Analytical modeling of quality parameters in casting process – learning-based approach

Suthar

Persis

Gupta

2022

IJQRM

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“…The alloy casted in various moulds like blast furnace slag, ferrochrome slag, red mud, olivine sand, and silica sand have hardness values of as 68HV, 67HV, 67HV, 66HV and 70HV, respectively. The Secondary Dendrite Arm Spacing (SDAS) value for slag mould casting is lower than that of casting using silica sand (Sinha et al, 2021).…”

Section: Introductionmentioning

confidence: 91%

“…LM6 aluminium alloy that was cast in a different mould sand was discovered to have a microstructure that contained a change in the size of the secondary dendritic arm spacing (SDAS) between -Al dendrites (Manjunathet al, 2019). The decrease in SDAS value results in improvements to the alloy's mechanical properties, such as increased strength and hardness, and a reduction in the inter-dendritic shrinkage porosity of the material(Sinha et al, 2021).…”

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confidence: 99%

Effective Utilization of Industrial and Constructional Solid Waste Materials in Foundry Mould Making to Prevent Environment Pollution and Conserve Natural Silica Sand

2023

Global NEST: The International Journal

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<p>Green sand moulding uses silica sand for metal casting. Silica sand mining and delivery to foundries destroy the ecosystem, making metal casting unsustainable. Due to increased sand-casting output and massive civil buildings in India, the silica sand supply is declining. The depletion and shortage of silica sand necessitate the search for viable replacements. Industrial solid waste from large-scale industrialization pollutes land, air, and water. In order to use industrial waste in large amounts, an attempt is made to use it as a replacement for natural resources. The main objective of this research is to reduce the consumption of silica sand in the foundry mould-making process. Silica sand is replaced with industrial solid waste, cupola slag, and construction solid waste sources like spent fire bricks and quarry dust, up to a considerable amount, to save the natural resources. Utilization of solid waste material in the mould-making process will reduce production costs and environmental pollution, like dumping solid waste materials on land. Sand tests like permeability, green compression strength, dry compression strength, and compactability were conducted to assess the moulding properties of these alternative moulding materials. The process parameters considered for this investigation were the percentage of bentonite binder and the percentage addition of alternative mould materials with silica sand. The various sand tests showed that 40%, 30%, and 20% of quarry dust, spent fire bricks, and cupola slag, respectively, will adequately replace silica sand for mould making. A bentonite binder of 8% is suitable for quarry dust mould, and a 10% bentonite binder is required for spent fire brick particles and cupola slag to yield better results. Aluminium castings were produced at the optimal mixture of these solid waste particles and silica sand. The results of mechanical tests such as hardness, tensile, and impact tests are comparable to those of silica sand castings.</p>

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“…In case sand molding is adopted, a distinct mold must be created for each produced piece. The materials composing a sand mold are usually silica, olivine sand, and sodium silica, along with other substances such as red mud and blast furnace slag [13]. By contrary, a permanent mold could be used for multiple pieces.…”

Section: Introductionmentioning

confidence: 99%

Energy-Saving Technology Opportunities and Investments of the Italian Foundry Industry

et al. 2021

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The foundry industry is regarded as one of the most energy-intensive industrial sector due to its energy consumption up to 9 MWh/ton of produced metal. As a result, many companies are trying to increase the energy efficiency of their foundry plants. Since many energy-saving technologies are proposed by manufacturers and the literature, choosing the most appropriate one is a difficult task. Moreover, being updated with the available energy-saving solutions is complicated because of the quick technology advances. Consequently, this paper aims at investigating the recent and future opportunities and investments for reducing the energy consumptions of the technologies of Italian foundry companies. Additionally, it aims at presenting a list of available technological solutions validated by Italian experts. To this end, the Energy Audits developed by 231 plants were analyzed to extract the implemented and planned interventions. Furthermore, the economic data available within the Energy Audits were studied to determine the advantages of a given technological solutions compared to the others. It emerged that the companies are strongly investing in increasing the efficiency of the auxiliary systems such as compressors and motors. The outcomes of this study can assist both researchers and energy managers in choosing the most appropriate energy-saving solutions.

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Influence of Mold Material on the Mold Stability for Foundry Use

Cited by 9 publications

References 26 publications

Analytical modeling of quality parameters in casting process – learning-based approach

Analytical modeling of quality parameters in casting process – learning-based approach

Effective Utilization of Industrial and Constructional Solid Waste Materials in Foundry Mould Making to Prevent Environment Pollution and Conserve Natural Silica Sand

Energy-Saving Technology Opportunities and Investments of the Italian Foundry Industry

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