If you're trying to use your captured data to suggest setpoints, system setups, recipes etc, there are two main options for how you can search for the values you need.

Fuzzy Matching uses smart search to find a time where you've made a similar product in the past.

AI Modelling uses a learning artificial intelligence to suggest what your settings should be.

Compared to AI results, Fuzzy Matching results…

• Are guaranteed to be reasonable and to have worked before,
• Can indicate if matches are exact or if there are differences (highlighting that the match is poor or that your situation is new),
• Are traceable - it tells you exactly which capture it matched with, and when it happened.

However, compared to Fuzzy Matching, AI…

• Is much better at predicting values in new configurations (within limits),
• Is able to compensate for a wide range of factors with much less information,
• Is able to run quickly, even with very large amounts of data to search
• Is more suitable for large 'problem spaces' (ie. situations with many analogue inputs).