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Mohammad Zandi

1 paper indexed

crossrefNext-Generation Digital Twins - Intelligence, Integration, and Innovation [Working Title]2026-04-23

Development of a Fast-Solving Machine Learning Surrogate Model for a Pharmaceutical Manufacturing Digital Twin

Mohammad Zandi, Donald Ntamo

High-fidelity models (HFMs) for twin-screw wet granulation (TSWG) are often too computationally expensiv//e for routine calibration, optimization, and digital twin deployment. This chapter presents a faster, cheaper, and easier-to-use surrogate modeling workflow that preserves HF…

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