Have AI monitor process data and suggest setpoints

Chemical plants monitor processes and suggest setpoints for consistent quality

Needs setupAI Act: no extra obligationsMonitoring sensor and machine dataChemicals & pharma

Fits: Production, engineering & maintenance

Process deviations are noticed before a batch goes out of specification. Shift supervisors and plant operators get reasoned suggestions for setpoints and decide themselves whether to adopt them.

Is this for you?

  • A product varies in quality, e.g. in viscosity, purity or colour, and you do not know exactly why.
  • The process control system and the laboratory have been storing measurements and lab results for at least a year, and these can be assigned to batches or points in time.
  • Operations, process development and plant safety can jointly support a project over several months.
First step today

Export the main process variables and the lab result for 15 to 30 completed batches of one product. Leave out the product name and formulation, give the variables neutral names and have the table evaluated with the template below. This shows whether your data reveals relationships and where effects cannot be separated.

How to go about it

  1. Define the plant, product and quality target
  2. Combine process data and lab values
  3. Have the model learn good batches as a reference profile
  4. Define warning and suggestion limits
  5. Bring suggestions into the control room
  6. Evaluate suggestions and false alarms

Templates to copy

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Included in the training

The complete guide

  • 6 steps explaining exactly what to do
  • 3 proven templates to copy into your own AI
  • Safe use: data, checking, deciding, informing
  • Pitfalls, effort and how to recognise success

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CP-07 · Legal status 08.10.2026