
Playbook
Furnace know-how: keep the recipe in the plant, not in two operators’ heads.
Reductant ratio and slag targets are often set by a few senior operators. When they are away, every heat is a gamble; when they retire, the plant relearns.

Reductant ratio and slag targets are often set by a few senior operators. When they are away, every heat is a gamble; when they retire, the plant relearns.
| Measure | What it tells you |
|---|---|
| Heats with complete data | Whether evidence exists to learn from |
| Handover notes captured as data | Whether shift knowledge is kept |
| Questions answered with citations | Whether people trust and use the record |
| Recipe changes tested on the model first | Whether trials are deliberate |
Furnace Twin is a physics model of your furnace (mass and energy balance, slag chemistry, reduction kinetics, an electrical model and furnace zones) calibrated on your heat history and re-calibrated as new heats arrive. It estimates energy, grade and recovery every heat and flags drift with its likely cause, such as basicity, reductant or electrodes. A scenario engine compares reductant, basicity, temperature and feed changes side by side so only the best goes to a short trial on the real furnace. Anyone on shift can ask questions in plain language and get answers that cite records, model runs and literature, and shift handover can be captured by voice in Hindi or English. Every model version is evaluated and logged. Delivery runs baseline, calibrate, then operate, starting with one furnace.
Collect data every heat, make shift handover structured, write down the targets operators use and why, gather past reports in one library, and answer questions with cited sources.
When the recipe lives with a few senior operators, results depend on who is on shift and the knowledge leaves when they do.
See it on your own data. Furnace Twin — Ask the furnace, see the proof. Book a 30-minute working session with an engineer.