Architectural and conceptual models for designing explainable, auditable and scalable industrial systems.
The Models section introduces ways of thinking that can be applied to real systems.
These are not implementation patterns or product architectures. They are mental models that help structure complexity.
Topics include:
- how GMP scales with proximity to the physical process
- why decisions must be treated as first-class architectural elements
- why context alignment is the hardest problem in Industrial AI
- what operational twins really are — and what they are not
These models help bridge IT, OT, data engineering, compliance, and AI into a single, coherent architectural view.
Why GMP requirements increase gradually with proximity to the physical process and how architecture often hides this gradient.
7 min read
Why modern systems must treat decisions as first-class architectural elements instead of implicit side effects of data processing.
7 min read
Why context alignment across time, batches and process phases is harder than prediction and determines AI success.
7 min read
Why operational twins focus on translating physical process reality into comparable, auditable representations.
7 min read