Our Insights

"Ignition v8.3 introduces a new public API that enables module developers to implement their own historians, making Ignition a platform for building historians." Here's what that means for you.

What batch analysis actually means, the methods teams use to compare and improve batches, and the one prerequisite most guides skip that decides whether any of it works.

SCADA historians are designed for operational access ie. high-frequency tag storage, real-time trend views, alarm history. They do that job well. They're not designed, however to handle long-term analytics, cross-system context, data access for teams outside the OT environment. That's a different job with different requirements.

Root cause analysis methodology takes twenty minutes. Finding the data to run it takes the other three hours. Here's why, and what actually fixes it.

How three fermentation and food & beverage giants replaced fragmented OT and IT systems with one unified data layer, and what became possible once they did.

Most factories already monitor energy at the site level. Rising energy prices mean that's no longer enough. This guide walks through how food manufacturers are moving from total-consumption monitoring to batch-level energy intelligence: what to meter, how to connect it to process data, and which KPIs actually drive action.

If you manage quality in a production environment, you already know the story. Operators run around the shop floor with paper checklists that are difficult to manage, or are completed hours after the actual check. At the end of the shift, someone has to manually type the results into Excel. By the time an issue surfaces, it’s usually too late: non-conformities slip through and nobody fully trusts the data. Today, with FactryOS v6, we’re changing that.

Factry Historian v8.1 furthers our mission to make industrial data easier to access, understand, and use with the launch of the MCP server. In doing so, Factry is connecting structured industrial data to the AI interfaces you already use. This release also brings a lot of refinement, consistency across the platform, and more robust calculations.

The case for using AI/LLMs in manufacturing is compelling to say the least. Imagine just asking your phone for the batch report for a batch that came back with a complaint, and getting the answer right away instead of having to sift through data or reports.