One of the most important concerns for manufacturers and retailers 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 i.e. from the point of harvest or 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 the threshold, it can destroy their nutrients, lead to their 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 very sensitive to temperatures and humidity excess.
In this article, we’ll discuss:
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 phases of the modern supply chain, including production, preparation, storage, and transport. This integration results in enhanced supply chain and logistics processes, which are commonly characterized as cold chain management.
Within the cold chain, cold storage management enables a rich set of value-added use cases, including:
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 the identification of 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 status of the products. 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, which may also result 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 for employing robust statistical processing over historic 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.
The typical application development workflow of an application that captures temperature anomalies in the cold storage process involves the following steps:
Disruptive Technologies provides a complete environment where such applications can be flexibly developed. Specifically, DT Studio facilitates reading data from DT temperature sensors, while at the same time linking to programming platforms (e.g., Python) for filtering their data and implementing the above-listed statistical processing functions. This provides a foundation for the fast and cost-effective development of cold storage intelligence applications.
Are you ready for the next step?
Access a practical example of temperature anomaly detection using DT sensors and our powerful DT Studio. The example is simple to follow and provides full details about how to lay down the foundation of a successful cold storage management application, including:
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