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Refrigeration cases and cooling systems consume roughly 1.3 quadrillion BTUs annually, accounting for about 7% of all commercial energy use in the U.S. From pharmacies and retail stores to healthcare labs, refrigeration ensures safety, compliance, and operational continuity. Yet, these systems are complex, energy-intensive, and can account for up to half of a facility’s total energy footprint. When refrigeration equipment fails, the impact can be staggering. For hospitals, temperature-sensitive medicines and materials can spoil within hours, leading to significant losses per incident in addition to the risk to patient safety. Perishable goods can quickly become unusable, resulting in wasted inventory and revenue loss. Beyond direct costs, there can be ripple effects such as emergency restocking and an impact on compliance status.
Refrigeration equipment also comes with a heavy operational footprint. In health-related facilities, medical-grade refrigeration cases and freezers require meticulous oversight because even minor failures can compromise patient safety. To mitigate the risk, maintenance teams perform periodic inspections and daily temperature checks. These critical systems demand proactive care to avoid costly downtime and compliance failures.
Willow transforms refrigeration management with a rich ontological representation of components and relationships in the Knowledge Graph. Using Activate Technology and a set of Skills that continuously monitor systems, Insights are generated and help optimize performance. Let’s dive in and take a closer look.
Refrigeration display cases are classified as either medium- or low-temperature. Medium-temperature cases keep contents refrigerated, while low-temperature cases maintain freezing conditions. This classification matters because analytics and performance benchmarks depend on it.
Modern systems often use a rack of compressors working as a group, sharing a common suction inlet and discharge manifold. Sensors monitor pressure and temperature at both points, with a goal of ensuring performance.
Each compressor may have telemetry such as run state and run level command. Refrigerant flows from compressors to the condenser, then through circuits feeding evaporators. Condensers also have telemetry for fan operation and temperature, referred to as the drop leg temperature. Circuits include control points, impacting all connected cases. Finally, the refrigerant loop closes as circuits feed back to the compressor group, creating an interconnected system that supports monitoring and optimization.
For further details, visit the github repo and sample.
Skills for refrigerated display cases play a key role in automated condition monitoring, working across fault detection and energy consumption.
Fault detection Skills are configured to continuously analyze telemetry from sensors connected to the display case. Some examples include temperature, pressure, compressor status, and defrost cycle readings. These Skills identify anomalies such as temperature deviations from setpoints, short cycling compressors, or extended defrost periods that could signal developing faults.
An example is Display Case Temperature Out of Target Range. This Skill monitors the temperature inside the refrigerated display case to ensure it remains within the designated target range. Several conditions can trigger this Skill. For instance, temperature sensors may report readings outside the preset cooling range due to an underlying cause like coil icing, a door left open, blocked vents, or failed components.
If the measured temperature falls outside the defined acceptable limits, i.e. too warm or too cold compared to the setpoint, the Skill triggers an Insight. This mechanism enables rapid identification of faults, helping facility teams prioritize maintenance and reduce operational disruptions.
Energy consumption monitoring Skills aggregate power and performance data, monitoring for signs of inefficiency. For instance, a Skill may analyze compressor on/off cycles, total run-time, and correlating case load with energy usage. If energy consumption deviates from normal baselines, e.g. excessive compressor run hours not explained by high load, an Insight is generated. Conditions triggering this Skill include failed door heaters, faulty anti-sweat controls, or poor defrost scheduling. Energy monitoring Skills can help quantify how much energy in kWh was saved and the corresponding impact on cost and carbon footprint.
An example is Display Case Defrost Running Too Often. This Skill monitors the frequency of defrost cycles in the display case. When the defrost heater operates more often than expected, the Skill generates an Insight indicating excessive energy usage and potential system inefficiency. Frequent defrost cycles can be triggered by high humidity, failed or misconfigured controls, overloading, or blocked airflow.
Another example is Display Case Evaporator Fan Over Design. This Skill monitors the evaporator fan operation, identifying instances where the fan is running at speeds or duty cycles that exceeds the design limits. This may be caused by the fan compensating for other faults such as poor airflow due to blocked or dirty coils or other sensor issues. It may also be due to the control sequence not being correctly adjusted for the current load or operating temperature.
Willow’s ontology-driven Skills and Insights are a key enabler in balancing safety with operational efficiency, compliance and sustainability. Organizations can resolve faults and inefficiencies proactively and minimize downtime. For facility teams, this turns refrigeration management from a cost center into a strategic advantage.