PROCESS INTELLIGENCE
Operational DNA learns from verified experience.
Process Intelligence connects verified experience with the context in which it was created. Step by step, this develops an operational knowledge model that can confirm, constrain and extend relationships.
Experience develops the operational DNA.
LEARNING WITH CONTEXT
A finding becomes a clear learning task.
Process Mining hands over a recurring relationship. Process Intelligence defines what should be tested using new comparable runs.
420+ uses operational DNA to describe the versioned knowledge and learning model that connects operational findings with their origin, context and scope of validity.
In the example, material group B repeatedly occurred together with a higher result in comparable runs. This does not yet support a general statement about the material. First, the change to be examined under known conditions is defined.
LEARNING TASKHow does the result change when material group B is used under comparable conditions?
VERIFIED OPERATIONAL EXPERIENCE
Real runs provide the learning and training foundation.
The learning task is tested under controlled conditions in the actual operation.
The operation defines what is deliberately changed and which conditions must remain comparable.
Product, batch, material, SOP version, execution, conditions, measurements, standardised images and result remain connected.
Suitable, professionally assessed runs can therefore serve as a training, comparison and validation foundation for operation-specific models.
Change material
Keep conditions comparable
Test the effect in new runs
VERSIONED OPERATIONAL DNA
Verified experience develops the knowledge model.
Every professionally assessed experience can confirm, constrain or extend the operation’s contextual model.
The knowledge model connects not only a result, but also its origin, context, evidence and known scope of validity.
Confirmed, disproved and only partially valid relationships refine what is already known and where the limits of that knowledge lie. Machine-learning models built on this foundation can be trained with suitable runs and tested against new data.
This gradually creates a versioned model of how products, materials, processes, conditions and results interact within this operation.
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01
LEARNING TASKDefine the relationship
Which relationship should be tested using new comparable runs?
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02
VERIFIED EXPERIENCEAssess the run in context
Change, context, run and observed result remain connected.
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03
REFINED KNOWLEDGE MODELDevelop operational DNA
The experience confirms, limits or extends the operational knowledge model.
NEXT STEP
Operational DNA creates value in the work itself.
The operation’s experience has created a growing, contextual knowledge model. The next step brings this knowledge into operational work – exactly where people assess situations and carry out work steps.