Free download

The adoption numbers, as a working file

Every figure from the 2026 report in one sourced spreadsheet: market sizing, use-case shares, barriers, and published deployment results, with the attribution column intact.

Done: your data pack is ready.

Download the Data Pack (.xlsx)

Read it alongside the full report.

What's inside

Market sizing 2024-2030 with source and CAGR math shown
Use-case share table and the GenAI trajectory (6% → ~25%)
Adoption-barrier data (45% expertise gap · 60% training investment)
Published deployment results with an explicit vendor-reported flag column

The TEEPTRAK approach

Machine learning in a factory starts with one data set: what each machine did.

Most use cases on this site need the same foundation: machine states, stops with reasons, cycle counts and scrap, recorded automatically and time-stamped. TEEPTRAK collects exactly that on any machine, and the plant gets live OEE from it long before a model is trained.

Machine states and cycle counts, time-stamped
Stop reasons entered by operators: the labels most data sets lack
Open export of the full history for data teams

Used in 450+ factories. At Hutchinson, OEE rose from 47% to 72%. Installed with a module wired into the electrical cabinet and a sensor at the edge of the line. No PLC changes. TEEPTRAK is not an MES: it measures, so you know what to fix first.

See how TEEPTRAK works →Map OEE data to ML features →