Estimation of Permeability of Green Sand Mould by Performing Sensitivity Analysis on Neural Networks Model

J Braz. Soc. Mech. Sci. Eng.

Bhushan

et al. 2019

Scarcity of high-cost silica sand, casting defect such as hot tear in hard moulds and casting ejection problem after solidification are the key industrial problems. Sawdust is a by-product of wood working industries, and economic disposal of sawdust in these industries is a growing concern to the wood industries. The present work utilized sawdust as an additive in preparing mould cavity for casting applications. Sand mould properties such as compression strength (CS), mould hardness (MH), gas evolution (GE), permeability (P) and collapsibility (CP) will have good impact on the quality of castings. The effect of variables, namely quantity of resin, hardener, sawdust and setting time, on no-bake furan-bonded sand system is studied in the present research work. The experiments are conducted as per design of experiments, and the data are used to investigate the effect of individual and combined parametric contributions towards responses and establish nonlinear input-output relationships. All nonlinear regression models (that is, input-output relationships) are found to be statistically adequate. The input-output relations are analysed and presented for each of the response with the help of surface plots. Further, the models are found to predict the output close to the experiment (target value). The grand average value in predicting responses is found to be equal to 5.03%. The multi-objective optimization of responses with conflicting nature (minimize: GE and CP; maximize: CS, P and MH) is carried out with the help of global fitness function values determined using genetic algorithm, particle swarm optimization, teacher-learner-based optimization and JAYA algorithms. The optimized values of process parameters that resulted in best set of responses are found to be equal to 60 min, 2.01%, 0.6% and 0.93% for setting time, quantity of resin, hardener and sawdust, respectively. Two automobile coupling parts are cast by pouring molten aluminium into the mould cavity with the optimized and non-optimum sand mould conditions. Further, these two cast components are tested for their quality characteristics, such as surface finish, yield strength, hardness, density and secondary dendrite arm spacing. It has been observed that the quality characteristics of castings produced in mould with optimized parameters are found to be much better.

Section: Introductionmentioning

confidence: 99%

“…bulk density, porosity, permeability (P), shear and compression strength (CS)). Porosity in castings was the result of trapping of air due to poor permeability [14]. The trapped air within the mould creates pressure when the permeability is not sufficient.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive modelling, analysis and optimization of furan resin-based moulding sand system with sawdust as an additive

Chate¹,

J Braz. Soc. Mech. Sci. Eng.

Bhushan

et al. 2019

“…15,16 Mold pressure was found to increase when the permeability was not sufficient and led to gas porosity in castings. 17 The permeability of molding sand depends on sand grain size and shape, clay content, water quantity, and degree of hardness. 17 The above observations lead to the conclusions that binder and hardener content, size and shape of mold sand, refining additives, and ramming influence the mold sand properties (permeability, mold hardness, compression strength, collapsibility, gas evolution, and so on), and thereby affect the dimensional accuracy, surface finish, mechanical, and microstructure of castings.…”

Section: Introductionmentioning

confidence: 99%

“…15,16 However, the molds with lower permeability will result in porous castings. 17 The influence of binder and hardener content on molding strength, gas evolution (GE), and casting microstructure was studied by researchers. [12][13][14] Molding strength improved with increase in resin content, but affected mold collapsibility resulting in hot tears.…”

Section: Introductionmentioning

confidence: 99%

Modeling and optimization of furan molding sand system using design of experiments and particle swarm optimization

Chate¹,

Proceedings of the Institution of Mechanical Engineers, Part E:

Deshpande³

et al. 2017

The present research work is focussed on establishing the complex nonlinear input-output relations of a furan resinbased molding sand system. Further, a set of input parameters, which will result in optimized mold properties, is determined. Grain fineness number, setting time, percentage of resin, and hardener are considered as process variables. Mold properties, such as green compression strength, shear strength, mold hardness, gas evolution, permeability, and collapsibility are treated as the process outputs. Nonlinear input-output relations have been developed and statistical analysis has been carried out by utilizing design of experiments, central composite design. Surface plots are developed to study and analyze the input-output relations. The input parameters that will result in best molding conditions and improve casting quality characteristics are determined by utilizing desirability function approach and multiple particle swarm optimization-based crowding distance (MOPSO-CD) techniques. The optimum value for the process variables namely grain fineness number, furan resin, hardener, and setting time are found to be equal to 55, 1.85, 1.2, and 60, respectively. The quality characteristics of the castings namely yield strength, ultimate tensile strength, hardness, density, and secondary dendrite arm spacing are found to improve by 14.03%, 15.08%, 14.14%, 12%, 2.22%, and 12.24%, respectively for the castings made in optimized molding sand conditions.

“…The sand grain size and shape was found to affect mould permeability and casting surface finish [8][9]. Casting porosity was reported to increase with the increase in mould pressure, and the compacted mould does not allow the generated gasses to escape out [10]. Kandelwal and Ravi [11] found that core shrinkage and hardness are significantly influenced by the amount of binder content, than hardener.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Optimization of Phenol Formaldehyde Resin Sand Mould System

Chate¹,

Archives of Foundry Engineering

Parappagoudar³

et al. 2017

Chemical bonded resin sand mould system has high dimensional accuracy, surface finish and sand mould properties compared to green sand mould system. The mould cavity prepared under chemical bonded sand mould system must produce sufficient permeability and hardness to withstand sand drop while pouring molten metal through ladle. The demand for improved values of permeability and mould hardness depends on systematic study and analysis of influencing variables namely grain fineness number, setting time, percent of resin and hardener. Try-error experiment methods and analysis were considered impractical in actual foundry practice due to the associated cost. Experimental matrices of central composite design allow conducting minimum experiments that provide complete insight of the process. Statistical significance of influencing variables and their interaction were determined to control the process. Analysis of variance (ANOVA) test was conducted to validate the model statistically. Mathematical equation was derived separately for mould hardness and permeability, which are expressed as a non-linear function of input variables based on the collected experimental input-output data. The developed model prediction accuracy for practical usefulness was tested with 10 random experimental conditions. The decision variables for higher mould hardness and permeability were determined using desirability function approach. The prediction results were found to be consistent with experimental values.