How To Track Anomalies & Set Alerts For Cold Storage Management

One of the most important concerns for manufacturers and retailers within the Cold Chain is to preserve the quality and ensure the safety of their goods. This means monitoring, controlling, and maintaining the appropriate temperatures of all perishable products. The optimal temperature should be maintained end-to-end or from the point of harvest/production until the product reaches the consumer. Failing to do so can harm the quality and environmental footprint of the production, along with added costs.

For example, if the temperature in food products increases beyond their particular threshold, it can destroy nutrients, lead to discoloring, and cause microbial growth. Furthermore, fresh products (e.g., fruits and vegetables) that become too hot must be discarded, which results in increased food waste and reduced environmental performance. The importance of monitoring temperature goes beyond the food chain. For instance, many medical products (e.g., drugs or vaccines) are susceptible to temperatures and humidity excess.

In this article, we’ll discuss:

• The benefits of cold storage management
• Reliable temperature alarms
• Capturing temperature anomalies using sensors

Cold Storage Management Benefits

To safeguard the quality of temperature-sensitive products, manufacturers and retailers integrate temperature auditing processes in their value chains. These processes are integrated into all modern supply chain phases, including production, preparation, storage, and transport. This integration results in enhanced supply chain and logistics processes, commonly characterized as cold chain management.

Within the cold chain, cold storage management enables a rich set of value-added Applications. These Applications include:

Product Quality and Safety

Cold storage management ensures that product temperatures remain consistent within specified margins. Specifically, cold storage actors are provided with timely and accurate information about temperatures that may compromise their products' quality. They can take relevant actions accordingly, like recalling palettes affected by high temperatures.

Energy Efficient Cold Storage

Cold storage is associated with high energy use. Energy consumption increases as enterprises attempt to ensure consistent temperatures during the transport of their products. Cold storage management solutions facilitate energy use optimization, considering the relative costs of cooling, heating, and temperature monitoring activities (e.g., cooling is usually more expensive than heating). Energy optimization is more challenging when logistic processes involve multiple products because each requires different temperature conditions.

CO2 Reduction and Environment Performance

Cold storage management activities also contribute to improved environmental performance. First, they minimize waste by reducing the number of products that need to be recalled or discarded. Moreover, they avoid “unmanaged” energy and optimize the CO2 emissions of cooling and heating activities.

Save Time & Enhance Productivity

Getting alerts whenever the cold storage shows temperature anomalies means employees don't need to conduct preventive maintenance activities automatically. This saves time and allows them to focus on more rewarding and creative tasks.

Brand Management

Most enterprises that put effective cold storage management solutions in place boost their brand image. For instance, retailers and manufacturers can assure their consumers that their products are sustainable, safe, and of high quality.

Reliable Temperature Alarms: The Foundation of Cold Storage Management

Implementing end-to-end temperature visibility and traceability is important but challenging. There are numerous parameters to consider, especially when monitoring the temperature for multiple products across different warehouses. Furthermore, the process of sharing and exchanging data across stakeholders with varying requirements can be a pain. However, before tackling supply chain complexities, cold storage implementations must deal with the ever-important physical world issues.

The most fundamental operation of a cold storage application is identifying when temperature limits have been breached. This may sound like a threshold monitoring operation, but it is much more complex than that. In practice, detecting a single temperature value that exceeds limits is not a reliable way for spotting cold storage problems.

Many events can lead to short, temporary temperature spikes that do not affect the products' status. For example, it is normal for logistics companies to open fridge doors regularly. Likewise, several OEMs (Original Equipment Manufacturers) integrate automated defrosting mechanisms in their products, resulting in temperature increases at certain intervals.

In this context, effective cold storage solutions must be able to identify important changes in the products’ temperature reliably while at the same time ignoring insignificant deviations. The identification of proper and significant temperature events is an integral part of most cold storage management applications.

There is a need to employ robust statistical processing over historical data. Specifically, instead of relying on a single temperature sensor, temperature alarms could be derived by calculating an entire envelope of values. These margins can then be used to determine whether important temperature changes have taken place.

Capturing Cold Storage Temperature Anomalies

The typical application development workflow of an application that captures temperature anomalies in the cold storage process involves several steps, including:

Sensor Deployment

Reliable sensing of the physical world is the most fundamental step to implementing temperature management applications. The accuracy and reliability of the sensors are, therefore, important parameters. Beyond credibility, long battery life, and an effective sensor installation are other aspects that can boost the economic efficiency of your cold storage management application.

Accessing and Pre-Processing Sensor Data

To detect temperature anomalies, there is a need for access to digital data about the product's temperature. The deployment of more than one temperature sensor is a sound basis for increasing the measurements' reliability. Nevertheless, it is also introducing the need for pre-processing sensor data to ensure they can be fed to the statistical functions of the following steps.

Defining the Temperature Event Envelope

Leveraging parametric methods and domain knowledge, this step specifies the limits beyond which a temperature event becomes significant. As soon as events remain within the specified limits, the temperature is considered safe and acceptable, even if some outliers are observed. However, values that are outside the envelope indicate a significant temperature anomaly and should be addressed.

Implementing Decision Functions for Detecting the Event

This step leverages the envelope definition to identify when excess temperature values indicate a real problem. In practice, it implements robust statistics that identify cases of different severity. For example, a warning could be issued in case a temperature value goes beyond the envelope, yet it is very soon restored. This could be a spike caused by a usual event (e.g., opening the door of a fridge). On the other hand, an alarm could be issued in case the excess value persists for a significant amount of time. Alarms and warnings are accordingly consumed by the cold storage management application.