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- W3200227040 abstract "Austempered ductile iron (ADI) has recently gained popularity over forged and cast steels for manufacturing of components used in heavy machinery, such as, automobiles, railways and farm equipment due to its high strength to weight ratio, casting capabilities and other attractive properties. The current industry practice for producing ADI is through the use of ADI standards. These standards specify grades of ADI with strength and hardness specified with a range for each grade. This grading system leads to precious alloying elements being wasted and also leads to increase in cost. In this study, a multilayer perceptron (MLP)-based forward modeling scheme is proposed to simulate the ADI process and accurately predict Vickers hardness number (VHN) of ADI based on the austempering process parameters and alloying element proportions. Then, using the trained MLP-based forward model and the particle swarm optimization (PSO) algorithm, a novel PSO-MLP-based inverse model has been proposed, which can predict the austempering process parameters and the alloying element proportions for a given VHN. With extensive simulation results, we have shown that MLP-based forward model can predict VHN of ADI with a mean absolute percent error of 0.21, which is much lower than a recently reported paper and the inverse model can accurately predict the ADI process parameters for a given VHN. This model can reduce wastage and cost by producing ADI with a specific VHN rather than within a range." @default.
- W3200227040 created "2021-09-27" @default.
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- W3200227040 date "2021-07-18" @default.
- W3200227040 modified "2023-09-27" @default.
- W3200227040 title "Inverse Modeling of ADI for Prediction of Process Parameters Using PSO-MLP Technique" @default.
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- W3200227040 doi "https://doi.org/10.1109/ijcnn52387.2021.9533566" @default.
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