Soft Sensors: Keeping an Inferred Measurement Honest
Choosing, validating, and maintaining inferential sensors that survive their first feedstock change.
Zoniax · Archive
Field Notes · Page 3
Field notes on industrial operations intelligence — sensors, edge telemetry, and machine learning for processing plants.
Securing Industrial Control Systems with IEC 62443
How to cut a processing plant into zones and conduits, set a security level for each, and build a boundary that actually holds.
Combustion Efficiency on a Waste-to-Energy Boiler
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.
Computer-Vision Quality Inspection: Five Myths
A vision cell sees what a tired inspector misses, but only if the engineering and the claims around it are honest.
Reheat Furnace and Rolling Mill Optimization in Steel
Where the hot end's energy, yield, and quality really trade off, and the instrumentation that holds the line.
CIP Optimization: Cut Water and Time, Keep the Clean
How instrumented return lines turn over-cautious clean-in-place cycles into measured ones, without ever shipping a failed clean.
Anomaly Detection on Process Data: Before the Alarm Trips
Fixed alarm limits catch the gross excursion and miss the early drift. Here's how learned anomaly detection scores raw sensor streams, and why the threshold, not the model, is the hard part.
Predictive Maintenance for Processing Plants
From sensor data to avoided downtime: how to choose where inference runs, how readings travel, and whether alarms come from rules or learned models.
ISA-95 in Practice: Wiring the Plant Floor to the ERP
How the standard maps the plant-to-business seam, what it actually standardizes, and where real integrations slip.
MTBF and MTTR: Four Myths That Hide Downtime
Reliability metrics are only as honest as the failure definition and the timestamps behind them. Four claims worth dismantling.
Process Historian vs Time-Series Database
Two ways to store plant data, compared by storage cost, query, integration, and fit — and how to tell which one your operation actually needs.
Edge vs Cloud for Industrial Analytics
Stop deciding edge-versus-cloud plant-wide. Decide it per workload, on latency, bandwidth, reliability, and who maintains it.