SAM4 Energy & Operations
Condition, energy, and operations data from one cabinet connection.
SAM4 measures current and voltage at the motor control cabinet. The same signal used for condition monitoring also shows how each motor runs, how much energy it uses, where losses occur, and when operation moves outside the expected profile. No extra asset sensors. No process instrumentation. No separate energy audit hardware.
Condition monitoring tells you when assets fail. SAM4 shows how they run.
Most condition monitoring focuses on failure risk. It does not show enough about daily operation: energy use, load profile, runtime, efficiency, and abnormal duty cycles.
That data is often split across SCADA, historians, energy meters, spreadsheets, or not captured at all. Teams see the energy bill, but not always which motors, stations, or operating patterns created the waste.
SAM4 closes that gap from the same cabinet measurement point. The current and voltage data used for condition monitoring also supports energy intelligence, operating metrics, and performance insight. One connection. No extra asset sensors.
Fault risk and severity
Detected faults, confidence level, severity, and recommended action across motors, drivetrains, and driven equipment.
Consumption, losses, and saving potential
Per-motor energy use, decomposed losses, and ranked saving potential against achievable efficiency.
Runtime, load, and duty cycle
Operating hours, starts and stops, load profile, and abnormal duty cycle events.
Find where energy is wasted, then drill down to why
Every view below is derived from current and voltage measured at the motor control cabinet. No flow meters, pressure sensors, or process-control integration required. Start at fleet level, rank the opportunity, inspect the asset, then validate how the machine is actually operating.
View 1 — Fleet overview
See total consumption, top consumers, and saving potential
The fleet view shows energy consumption in kWh, saving potential in MWh, and the assets driving most of the energy use. Ranked charts show where to investigate first.
Use it to answer: where should we focus first?
Action: select assets for investigation.
View 2 — Saving potential
Rank every asset by energy opportunity
The saving potential view ranks every monitored asset by rated power, actual consumption, energy losses, and efficiency percentage. Each asset is flagged High, Medium, or Low based on the gap between current and achievable performance.
Use it to answer: which assets are worth investigating?
Action: prioritise energy projects.
View 3 — Asset-level efficiency
See where this asset loses energy
Asset-level views break total consumption into useful work and losses, with components for supply losses, motor losses, and driven-equipment losses. A timeline tracks how efficiency changes over weeks and months. Benchmarking compares the asset against industry best practice.
Use it to answer: where is energy being lost?
Action: identify the likely loss source. Your domain expertise explains why.
View 4 — Pump performance
See where the pump runs on its curve
For supported centrifugal pump configurations, SAM4 estimates operating point, head, flow, and mechanical power from the electrical signal. It plots the operating point on the pump curve and shows the time spent near or away from best efficiency point.
Use it to answer: is the pump running in its efficient operating zone?
Action: validate control, duty point, or pump sizing. Accuracy depends on pump curve quality, operating range, motor data, and stable measurement conditions.
How SAM4 estimates load, speed, efficiency, and saving potential
SAM4 measures electrical input power at the motor control cabinet. It does not measure shaft power directly. Instead, it estimates efficiency from the electrical signal, motor data, and known relationships between active power, load, speed, and motor efficiency.
Load from active power
SAM4 measures current and voltage and calculates active power, accounting for the phase relationship between them. For three-phase motors, active power is strongly related to motor load. SAM4 maps the measured active power to a load percentage using the motor's nameplate data and operating history.
Speed from frequency
For VFD-driven motors, supplied frequency determines motor speed. SAM4 can derive speed from measured electrical data. In earlier analyses, the VFD voltage-to-frequency relationship was used where direct frequency tracking was not yet available. For non-VFD motors, speed estimation depends on motor configuration and operating data.
Efficiency from load, speed, and motor class
Motor efficiency depends on rated power, load, speed, and efficiency class. With load and speed estimated, SAM4 compares the asset's operating profile with standard motor-efficiency behaviour to estimate efficiency and energy use.
Saving potential from the operating profile
SAM4 uses historical operating data to identify oversized motors, inefficient operating points, and assets running outside their efficient load range. Saving potential is estimated by comparing current consumption with the expected consumption after rightsizing or operating closer to the efficient range.
This method turns condition-monitoring data into an energy-efficiency screen across the fleet. It is an estimate, not a direct shaft-power measurement, and it does not replace a detailed engineering audit. It shows where to look first and which assets are likely to justify deeper investigation.
Download the full whitepaper: Using SAM4 to help drive sustainable industry →
What SAM4 shows. What your team decides.
SAM4 shows where energy, operating, and performance issues are likely to exist at asset level. Your team adds the process context: production demand, control strategy, safety limits, maintenance windows, and capital plans.
Asset-level evidence and prioritisation
Asset-level measurement · estimates · trends · rankings · alerts
Process context and decisions
Process context · operational constraints · control strategy · investment decisions
| Area | SAM4 shows | Your team decides |
|---|---|---|
| Energy efficiency | Per-motor energy consumption, estimated losses, efficiency trend, and saving potential. | Why the asset runs inefficiently, and whether setpoints, operating windows, or equipment changes are possible. |
| Pump performance | For supported centrifugal pumps: estimated operating point relative to BEP, plus head, flow, and mechanical power estimates from the electrical signal. | Whether the issue is system curve, process demand, pump selection, throttling, or control strategy. |
| Operations | Runtime, starts/stops, load profile, duty cycle, and detected abnormal operating events such as dry running, cavitation, or reverse rotation. | Which operating patterns to change, and whether shifts in scheduling, sequencing, or demand response are feasible. |
| Asset profile | Estimated motor load, speed, mechanical output power, and operating profile per asset. | Whether to resize motors, retrofit VFDs, replace assets, or change duty allocation. |
| Power quality | Voltage, current, power factor, imbalance, and harmonic indicators across monitored motors. | Whether to escalate to the utility, install corrective equipment, change drive settings, or accept the variance. |
| Integration | Energy, performance, and operational metrics available via API for SCADA, historians, dashboards, and digital twins. | Which systems receive the data, how often, and which events should trigger action. |
Energy optimisation is rarely solved by data alone. The right action depends on the process the asset serves.
SAM4 gives your engineers the evidence and prioritisation. Final optimisation decisions still depend on process knowledge, operational constraints, and local engineering judgement.
Measured efficiency gains. Validated at scale.
Vitens: 7.1% station-level efficiency gain after a three-pump control change
At Vitens’ Hoenderloo production facility, SAM4 monitored 17 pumps: nine borehole pumps and eight clean-water distribution pumps. The data showed that two 55 kW distribution pumps were oversized during low-flow periods and operating at 69% efficiency.
SAM4 identified the opportunity. Vitens applied the process knowledge. The team adjusted the changeover threshold and increased the speed of a smaller 11 kW pump. The result: efficiency gains of 5.2% to 11.5% across the three pumps, a 7.1% station-level improvement, and an estimated 9.2 tCO₂ reduction per year.
“There is a lot to gain from improving the pumps’ operational efficiency while still meeting demand.”
ERGO: validated across 1,000 motors over three years
ERGO was a research programme led by the Institute for Sustainable Process Technology, with partners including Nouryon, Vopak, Vitens, Huntsman, and Utrecht University. Samotics installed monitoring on 1,000 motors across water and chemicals sites between 2020 and 2023.
The programme developed and validated the efficiency models now used in SAM4. Across the monitored fleet, ERGO identified 10–20% energy-saving potential and validated the motor-rightsizing methodology on 303 industrial motors.
SAM4 is not an energy audit dashboard. It uses continuous electrical data to identify where energy is being wasted, rank the opportunity, and give engineering teams the evidence to change operation, controls, or asset configuration.
13 metrics from one cabinet measurement point
Every metric below is derived from current and voltage measured at the motor control cabinet. Some are measured directly, some are calculated from electrical power, and some are estimated using motor, drive, and asset models. No flow meters. No pressure sensors. No additional asset-mounted hardware.
Electrical and energy metrics
| Metric | Type | What SAM4 shows | Why it matters |
|---|---|---|---|
| Current | Measured | RMS current per phase | Detects imbalance, overload, underload, and abnormal operating conditions |
| Voltage | Measured | Phase and line voltage behaviour across the motor supply | Shows supply-side issues, imbalance, and voltage variation |
| Supply frequency | Measured / derived | Grid or VFD output frequency | Supports speed estimation and operating-mode analysis |
| Power and power factor | Calculated | Active, reactive, and apparent power; power factor | Shows useful power, reactive demand, and inefficient electrical operation |
| Energy consumption | Calculated | kWh per monitored asset over time | Enables asset-level energy allocation and cost visibility |
| Energy losses | Estimated | Supply, motor, and driven-equipment loss estimates | Helps identify where energy is being lost |
Operational and performance metrics
| Metric | Type | What SAM4 shows | Why it matters |
|---|---|---|---|
| Runtime | Calculated | Actual operating time per asset | Verifies duty cycle and supports maintenance planning |
| Starts and stops | Calculated | Number and timing of start/stop events | Reveals cycling behaviour, fatigue risk, and control issues. Frequent starts can increase electrical and mechanical stress, depending on drive setup and starting method. |
| Motor load | Estimated | Percentage load over time | Identifies oversized motors and duty-cycle mismatch |
| Motor speed | Estimated / derived | Operating speed or RPM estimate | Supports load, efficiency, and pump-performance analysis |
| Mechanical power | Estimated | Estimated shaft output power | Enables load profiling without a torque sensor |
| Pump head and flow | Estimated | For supported centrifugal pump configurations: head and flow estimates from electrical data and pump/motor information | Provides process-side insight without flow or pressure sensors |
| Pump operating point / BEP | Estimated | Estimated time spent near or away from the best-efficiency operating zone | Reveals throttling, oversizing, and inefficient pump operation |
Direct, calculated, and estimated metrics are shown separately. Pump-performance metrics depend on pump type, available asset data, operating range, and signal quality. SAM4 is designed to identify and prioritise energy opportunities; final optimisation decisions require process context.
Metrics are available in the SAM4 dashboard, via the SAM4 API, and through exports to historians, SCADA, dashboards, or enterprise data platforms. Validated actions can route into CMMS workflows.
No extra asset sensors. No separate energy metering project.
If SAM4 already monitors your assets, energy and operations intelligence can be enabled from the same cabinet measurement point. The current and voltage data used for condition monitoring also supports energy, performance, and operational metrics.
One measurement point, three data streams
SAM4 uses the same current and voltage measurements to support condition monitoring, energy intelligence, and operational visibility. No flow meters, pressure sensors, or asset-mounted hardware required for the standard energy views.
Fleet-wide by default for monitored assets
Once standard asset data is available, SAM4 calculates energy, operational, and performance metrics across monitored assets. No per-asset instrumentation project. No separate metering rollout.
VFD-aware efficiency estimates
SAM4 accounts for VFD-driven operation when estimating speed, load, and efficiency. Drive setup, nameplate data, and signal quality are reviewed during onboarding.
Benchmarked against standards and fleet peers
SAM4 compares motor efficiency against IE-class references and asset performance against fleet averages. The benchmark shows where an asset performs above or below expected efficiency.
Energy optimisation still requires process expertise. SAM4 gives your team the asset-level evidence: where energy is used, where losses appear, and which assets deserve investigation first.
See how each asset actually runs
SAM4 derives runtime, starts, stops, and abnormal operating patterns from current and voltage at the motor control cabinet. That gives you an independent operating record for every monitored asset, without PLC integration or manual logging.
How long did it actually run?
Track actual operating time per asset, per day. Use it to verify duty cycles, plan maintenance windows, and compare runtime assumptions against SCADA, PLC, or operator logs.
ActionAdjust maintenance planning based on actual duty, not assumed duty.
How often is it cycling?
SAM4 counts starts and stops and flags assets that exceed expected thresholds. Frequent cycling can increase electrical and mechanical stress, depending on drive setup and starting method.
ActionReview control logic, duty allocation, and sequencing.
When did it run outside the expected envelope?
SAM4 identifies abnormal operating patterns such as dry running, cavitation, reverse rotation, and operation outside the design envelope. Each event is logged with timestamp and duration.
ActionInvestigate root cause and prevent repeated damaging operation.
In the dashboard
Per-asset operational profile from the electrical signal
Running hours, start and stop counts, and abnormal operating events with timestamps and durations. The same view is available for every monitored asset, with no PLC integration or manual logging.
SAM4 shows the operating pattern. Your team uses process context to decide whether the pattern is expected, inefficient, or harmful.
Asset-level motor data for your systems, models, and teams
SAM4 is not a closed dashboard. Every monitored motor becomes a structured data source for condition, energy, runtime, load, speed, power, and operating behaviour. Maintenance teams get validated actions. Operations teams get asset-level operating data. Data teams get more variables for models, optimisation, and digital twins.
Feeding into your digital platform
Maintenance workflows
Fault type, severity, evidence, recommended action, and status routed into CMMS (SAP PM, IBM Maximo, Infor, or similar).
For maintenanceSCADA, historians, dashboards
Runtime, starts/stops, energy, load, speed, and efficiency as time-series exports into the systems your operations teams already use.
For operationsData science and digital twins
Motor-level variables for model calibration, energy optimisation, anomaly analysis, and asset-performance modelling.
For data teamsAPI and exports
Structured access by asset, timestamp, site, and metric type through authenticated APIs and scheduled exports.
For platformSAM4 adds motor-side operating evidence. Your teams combine it with process, production, and maintenance data to make better decisions. SAM4 does not replace process instrumentation where direct flow, pressure, or product-quality measurements are required. See integrations and data access →
Energy management is moving from periodic audit to continuous evidence
New energy rules are increasing the need for measured, asset-level energy data. SAM4 does not make a site compliant by itself, but it gives engineering, energy, and compliance teams the motor-level evidence they need for audits, ISO 50001 programmes, and efficiency projects.
EU Energy Efficiency Directive
Audit and energy-management obligations. Companies above 10 TJ average annual energy use fall under energy-audit obligations. Companies above 85 TJ must introduce an energy management system. SAM4 supports this with per-motor consumption, load profiles, runtime, and saving-potential evidence.
ISO 50001
Continuous improvement needs continuous data. ISO 50001 turns energy management into a structured improvement system: significant energy uses, baselines, performance indicators, action plans, and management review. SAM4 adds continuous motor-level data to support that process.
US DOE motor-efficiency standards
Better decisions for motor replacement and retrofits. New DOE electric motor efficiency standards apply from June 1, 2027. SAM4 helps identify inefficient operation, oversizing, and assets where replacement, rightsizing, VFD retrofit, or control changes may create value.
SAM4 is not a compliance certificate. It is measurement infrastructure: asset-level energy, load, runtime, and efficiency data your teams can use to prove where energy goes, prioritise measures, and track improvement.
Requirements differ by country and asset scope. SAM4 supports measurement, evidence, and prioritisation; customers remain responsible for compliance decisions.
See what your motors actually do
Request a demo to see energy, operational, and performance data from your own fleet. If SAM4 is already installed for condition monitoring, these data streams are one configuration step away.