A Business ML model trained on a synthetic paracetamol production dataset to estimate process costs. This proof-of-concept demonstrates how neural networks can outperform spreadsheets in accuracy, flexibility, and insight.
🚀 Try the Paracetamol Model →
📖 Article under publication review at AIChE
A Business ML model trained to estimate multi-step cost components in CMOS semiconductor fabrication. This work highlights the potential of neural networks to replace static formulas and improve margin clarity in high-variability operations.
🚀 Model under live deployment migration
📖 Read the Article →