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.
Abstract. The quality of the castings are depended on many properties of sand mould like mould hardness, green compression strength, shear strength etc. and these properties in turn dependent on factors such as grain fineness number of sand, setting/curing time, amount of resin, amount of hardener, moisture content etc. Mould hardness is very important while transferring mould from moulding station to pouring station when the weight of the mould is above 100kg and may lead to defects. In the present work, an effort is made to study the mould hardness of a moulding sand specimen using Taguchi technique.L9 orthogonal array is used and experiments are conducted randomly. The main factors such as the amount of resin, amount of hardener and setting time were considered. Factors were selected based on Literature review and brainstorming session with foundries. The chemical (resin and hardener) used is alphas set type two part system. From experiments, it was observed that the Amount of resin and setting time are significant for mould hardness. Confirmation tests were conducted to validate the obtained results.
Purpose This study aims to examine factors that determine the adoption of additive manufacturing by small- and medium-sized industries. It provides insights with regard to benefits, challenges and business factors that influence small- and medium-sized industries when adopting this technology. The study also aims to expand the domain of additive manufacturing by including a broader range of challenges and benefits of additive manufacturing in literature. Design/methodology/approach Using data collected from 175 small- and medium-sized industries, the study has examined through Mann–Whitney test to understand the difference between owners and design engineers on additive manufacturing technology adoption in small- and medium-sized companies. Findings This study suggests contribution to academic discussion by providing associated factors that have significant impact on the adoption of additive manufacturing technology. Related advantages of additive manufacturing are reduction in inventory cost, lowering the wastage in production and customization of products. The study also indicates that factors such as cost of machinery, higher level of cost in integrating metal components have a negative impact on the adoption of this technology in small- and medium-sized industries. Research limitations/implications Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further in the field of challenges and growth in other areas of application of additive manufacturing, for instance, medical sciences, fabric and aerospace. Practical implications The study provides important implications that are of interest for both research and practitioners, related to technology management in small- and medium-sized industries, e.g. foundry and machining industries. Social implications This work/study fulfills an identified need of the small- and medium-sized companies in adopting new technologies and contribute to their growth by understanding the need to accept and implement technology. Originality/value This paper fulfills an identified need to study how small- and medium-scale companies accept new technologies and factors associated with implementation in the manufacturing process of the organization.
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Green sand casting is treated as the most versatile casting process due to their excellent design flexibility that offer complex shapes and ability to reclaim silica sand. The modern foundries are looking for alternate moulding materials to partially replace the high cost silica sand. Cow dung is a naturally available eco-friendly binding as well as additive material and is used to partially replace the silica sand. Improper choice of the combination of moulding sand variables, such as degree of ramming, percentage of cow dung, percentage of clay, and percent of water will affect the moulding sand properties and thereby quality of casting. In the present work, Taguchi method is employed to plan and conduct experiments. Pareto analysis of variance is performed to know the contribution of variables on the moulding sand properties (i.e. compression strength, permeability, loss-on-ignition). Taguchi DEAR method is used to determine the single optimal levels of input factors that enhances the performances of all the sand mould properties. Percent of clay and cow-dung found to be the most dominating factor towards all the sand mould properties.
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.
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