AI is not the solution when the process is not understood
AI fails long before the model.
If a factory cannot answer:
- what happened
- when it happened
- in which recipe phase
- and how it compares to previous cycles
then AI has nothing to work with.
Where real improvements come from
The strongest gains in Industrial AI rarely come from complex models.
They come from:
- comparing the same phase across batches
- detecting slow drifts over long windows
- aligning late or asynchronous signals correctly
These approaches outperform deep learning when clarity exists.
AI becomes powerful only on a solid foundation.
