OpsNous

A soft sensor (software sensor) uses predictive algorithms to infer critical process variables — such as product composition or quality — in real time, based on data from existing physical sensors (like temperature, pressure, and flow rates). They provide continuous quality estimation without the high maintenance costs, latency, or reliability issues of hardware analyzers.

Most process plants still depend on grab samples and laboratory analysis for critical quality variables. By the time the result arrives, the process has often already moved. OpsNous builds real-time soft sensors that continuously estimate those quality variables from the high-frequency data your plant already collects, so operators see product quality updating every few seconds instead of every few hours.

Online analyzers frequently go offline. During that period many plants drop to manual control or freeze the last good value, increasing variability and risk. OpsNous acts as a reliable hot-standby soft sensor. It continues providing accurate estimates while the physical analyzer is unavailable, keeping closed-loop control running without interruption.

Grade transitions are one of the biggest sources of off-spec material because quality feedback arrives too late. OpsNous delivers continuous soft-sensor estimates of key quality parameters (such as melt index or composition). This gives operators and APC systems real-time visibility so they can make smoother adjustments and significantly shorten transition times.

Conventional alarms usually trigger only after a deviation has already grown large enough to matter. OpsNous continuously monitors process behavior and flags subtle drifts hours before they reach alarm thresholds, giving operators time to make small corrections instead of reacting to upsets.

Yes. Soft sensors use existing process measurements (temperatures, pressures, flows, etc.) to estimate hard-to-measure quality variables in real time. Systems Intelligence Labs specializes in building and deploying these soft-sensor frameworks through OpsNous, trained on your own plant data.

Process plants drift — heat exchangers foul, catalysts deactivate, and operating conditions change. Static models gradually lose performance. OpsNous includes continuous monitoring against laboratory results and adaptive mechanisms that keep the soft sensors aligned with current plant behavior over long periods.

Too many low-value alarms cause operators to miss genuine problems. OpsNous cuts through the noise by prioritizing meaningful process deviations with confidence scores and context, helping teams focus only on what actually needs attention.

Delayed or intermittent quality feedback forces teams to leave large safety margins, which costs yield and energy. Reliable soft sensors from OpsNous reduce that uncertainty by providing continuous, validated estimates, allowing safer operation closer to constraints.

Final quality testing often happens too late to save a batch. OpsNous can be configured for online batch classification and early abnormality detection, helping teams intervene before the batch is completed.

An online analyzer is physical hardware that measures a variable directly (with maintenance, calibration, and cost). A soft sensor is a software model that estimates the same variable from other available measurements. OpsNous specializes in building high-accuracy soft sensors that complement or back up physical analyzers.

Flare events are often the downstream result of upstream process upsets that were not detected early enough. OpsNous correlates process drifts across units and provides early warnings, helping reduce the frequency and duration of unplanned flaring.

Yes. Soft sensors are particularly valuable where physical sensors cannot survive or are impractical. OpsNous has been applied in such environments by combining secondary measurements (shell temperatures, motor current, pyrometry, etc.) to estimate critical quality variables continuously.

Manual reconciliation is slow and usually happens after the opportunity to act has passed. OpsNous automatically aligns multi-rate data, builds the soft-sensor models, and surfaces only meaningful deviations with context — shifting engineers from data chasing to process improvement.