Industrial Data Governance: Owning OT Data
Who owns the data your machines produce, who may see it, and how to keep it trustworthy from the sensor to the boardroom.
Zoniax · Archive
Field notes on industrial operations intelligence — sensors, edge telemetry, and machine learning for processing plants.
Who owns the data your machines produce, who may see it, and how to keep it trustworthy from the sensor to the boardroom.
Why specific energy consumption is the metric that actually exposes plant efficiency, and how to benchmark it without lying to yourself.
Five things vendors and managers get wrong about cold chain temperature monitoring, and what actually catches an excursion in time.
Where machine vision, soft sensors, and predictive maintenance actually have to run on a regulated production line.
Telling a synchronized twin from a dashboard, and a four-line test for whether a process plant should build one.
Cameras grade scrap by sight, but it takes spectroscopy to read the copper that wrecks a heat, and a control loop to act before the grab closes.
How the EU's NIS2 directive turns into concrete OT controls on a processing plant floor, built in the order that actually works.
Continuous emissions monitoring isn't one technology. Pick extractive, in-situ, or predictive on accuracy, latency, availability, and who maintains it.
Choosing, validating, and maintaining inferential sensors that survive their first feedstock change.
How to cut a processing plant into zones and conduits, set a security level for each, and build a boundary that actually holds.
Why squeezing the burn on a plant that runs on garbage is a control problem you fight every shift, not a setting you dial in once.
A vision cell sees what a tired inspector misses, but only if the engineering and the claims around it are honest.