Three tools that read a plant's own historian export and say what changed, when, and which of it is worth acting on — with the evidence printed beside every conclusion, including what it could not settle.
Each answers one question. None of them assumes a model of how your plant should behave: normal is learned from your plant's own history.
Is the data good enough to trust, when did the plant leave normal operation, and which of those departures are worth acting on?
Which batches did not run like a good one, where in the batch did they diverge, and which tag took them there?
This loop is cycling — is the cause inside it, or is it only passing on someone else's problem?
An assessment is only useful if someone can disagree with it. Every report here is built so that they can.
See for yourself. The worked examples run all three tools on public and anonymised data, including benchmarks where the faults are known in advance, so every claim on this site can be checked against a result.
Assessment tells you what is wrong. Procedure automation is a large part of what you do about it — and ISA-106 is the standard that says how.
A fifteen-chapter summary edition covering the three models, automation styles, the lifecycle management strategy, and the procedure automation lifecycle from specification through to retirement.
The full edition is in process to be published. Ask for a draft.
Send a few days of historian export and a tag list. The first conversation is about whether the data can answer your question at all.