Industry · Food & Beverage Manufacturing
Your production line has a fingerprint. The signals that precede a batch failure are in your data.
Cold chain drift, batch inconsistency and food safety events leave patterns in time-series data before specification limits are crossed. Eyer learns what normal looks like for your operation and surfaces deviations before they become consequences.
The food & beverage challenge
High-consequence deviations. Dense process data. Compliance requirements.
Cold chain drift that precedes quality events
Refrigeration drift, temperature stratification and compressor efficiency decay leave patterns in the data before any product quality event. By the time a threshold alarm fires, you are responding to a consequence, not a cause.
Batch inconsistency traced to upstream process drift
Raw material variation, blanching and cooling cycles, mixing and dosing sequences create correlations invisible to individual threshold alarms. Eyer maps the dependency between upstream signals and downstream quality outcomes.
Regulatory traceability that requires more than alarms-and-responses
Food safety auditors and certifiers increasingly require timestamped operational evidence, not just compliance records. Eyer produces a contextualised audit trail per sensor, per batch, per event.
What Eyer can detect in food & beverage operations
The patterns that precede production events are detectable before specification limits are crossed.
Refrigeration drift, compressor efficiency decay, blanching and cooling deviations, mixing and dosing inconsistencies: these signals appear in time-series data before any product quality event is visible. Eyer learns three dynamic baselines per metric, adapting to batch cycles, seasonal raw material variation, and production schedules. No manual threshold configuration.
How Eyer applies to food & beverage operations
Three steps from your historian to operational intelligence.
Connect without new infrastructure
Eyer handles any time-series data: OT, IT, or IoT. Data from your historian, SCADA, MES, or any time-series source reaches Eyer without new sensors or PLC access. OPC-UA, Modbus, MQTT, InfluxDB and 300+ input plugins.
Fingerprint learning adapts to your production cycles
Eyer builds three dynamic baselines per metric, adapting to batch cycles, seasonal raw material variation, and production schedules. No manual threshold configuration.
Alerts before specification limits are crossed
Alerts arrive before any specification limit is breached, with root cause context, correlated signals, and recommended action. A decision-ready briefing, not a data dump.
Run Eyer on your production historian
Connect your existing data. First findings within one week. No new sensors, no PLC access, no disruption to your operation.
See if Eyer fits