Predictive Modelling of Time-Dependent Green Sand Moulding Parameters Using the Taguchi Method
DOI:
https://doi.org/10.24425/mper.2025.157215Abstract
Green sand mould quality plays a pivotal role in casting reliability and dimensional accuracy, yet mould properties degrade over time due to environmental exposure and production delays. This study examines the time-dependent behaviour of critical mould characteristics – green compressive strength (GCS), mould hardness, and permeability – under varying process conditions. Using a Taguchi L27 orthogonal array, the effects of moisture content, ramming time, and holding time were systematically evaluated across 27 experimental setups, with sequential moulding under realistic foundry conditions. Regression models were developed to predict property degradation based on mould age, which is defined as the cumulative moulding and holding time. Results highlight that optimal property retention occurs at moderate ramming times, higher moisture content, and shorter holding periods. Case 2 (4% moisture, 5-second ramming, 10-minute holding) demonstrated the most favourable balance of strength, hardness, and gas permeability. The predictive models exhibited high accuracy (R2 > 0.94), supporting their data-driven mould quality control application. These findings offer practical insights to improve maintainability, reduce casting defects, and enhance process reliability in sand casting operations. The research contributes to the broader goals of sustainable manufacturing and production system optimisation through statistically guided process management.References
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