Data flow
Historian, SCADA, MES, ERP, LIMS, and laboratory data. Normalization, measurement units, and signal quality.
Physics-first industrial intelligence
REAL DARK FACTORY
A unified digital twin for a steel plant: asset models, live telemetry, quality forecasting, and scenario optimization.
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01 / Definition
A path to the dark factory. Not a marketing teleport.
GSOS contains the essential foundation for lights-out manufacturing: a connected digital twin, telemetry, physics-first models, forecasting, and optimization. Autonomy emerges step by step after accuracy and safety are validated.
First the system explains and recommends. Then it controls.
For steelmaking, the honest starting point is an advisory layer for one process route. The operator sees the causes, compares scenarios, and approves an action. Closed loop is possible only after reproducibility is proven.
01
Observe
Collect signals and verify their quality.
02
Predict
Calculate the state and forecast KPI.
03
Advise
Recommend a scenario and explain why.
04
Automate
Increase autonomy only after validation.
02 / Architecture
From process physics to a verifiable decision.
Every calculation must leave a trace: input data, model version, applicability limits, operator recommendation, and actual outcome.
Model Registry
Formula versions, parameters, calibration, applicability limits, and reproducible calculations.
Plant Graph
Assets connected through material, energy, and information flows.
State Engine
The current calculated state and forecast for the selected process route.
Scenario Lab
What-if scenarios for raw materials, operating modes, energy, time, equipment, and constraints.
Control Room
Deviation causes, recommendations, operator approval, and a complete decision log.
The first measurable result
One process. One KPI. Proven impact.
Not the entire plant at once. We select an asset or route with available data, clear physics, and a measurable outcome: quality, energy, yield, cycle time, or CO₂.
01
Pilot definition
Process boundary, assets, roles, signals, KPIs, constraints, and accuracy criteria.
02
Data readiness
History, frequency, gaps, measurement units, and a read-only gateway across the OT/IT boundary.
03
Physics-first PoC
A versioned model, calibration, and verification against an agreed set of historical cases.
04
Scenario Lab
A baseline and two or three what-if scenarios with forecasts and confidence intervals.
05
Human in the loop
The operator accepts or rejects a recommendation; the system records the decision and actual outcome.
Clickable prototype
A control room you can already explore.
The demo interface presents a plant graph, mock telemetry, quality forecasting, and scenario mode. It is not connected to a real plant; it is a working model of the future flow.
Launch simulationQuality forecast96.4%+1.8%
Energy intensity472kWh/t
Model confidence91%validated
RAW
FURNACE
LADLE
CASTING
QUALITY
03 / Similar cases
Similar company cases
Manufacturing, accounting, integrations, process management, AI, and systems architecture are the capabilities that turn a complex domain into a working product.
ManufacturingPrime EVA
A manufacturing and accounting backbone with integrations, inventory, and internal operations.
Operations backboneFORMA WMS + BPM
Batches, materials, inventory movement, statuses, rules, and controlled enterprise processes.
ArchitectureFRACTAL
Architecture of complex systems where the data model and interfaces are designed as one product.
AI + SaaSVorfahr
A production SaaS platform with an AI layer, integrations, and manufacturing logic.
Recommended start$7 600up to 2 months · extended system design
Commercial route
Design the proof first. Estimate the industrial system next.
The available data is not enough for an honest estimate of the complete GSOS. The first paid phase turns the idea into an architecture, model registry, prototype, PoC criteria, and a basis for a fixed-price estimate.
ScopePilot route, KPIs, and out-of-scope
ArchitectureOT/IT, data gateway, models, and audit
PrototypeControl room and scenario lab
PoC planData, test cases, and accuracy
Technology context: Siemens — Lights-out factory · NVIDIA — Industrial Facility Digital Twins. The project language is based on the supplied GSOS brief; actual plant characteristics require validation.
Next step
Get the data. Select the process. Prove the model.
An NDA, the plant documentation package, and a 90-minute technical workshop are the next rational step toward Real Dark Factory.
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