Maintaining the health of laboratory refrigeration assets is crucial to protecting the integrity of life-saving drugs and vaccines. To keep them safe, storage facilities often rely on N+1 redundancy, widely regarded as the gold standard for protecting stored products in the event of refrigeration failures. But something fascinating has happened in recent years that challenges the reliability of N+1 redundancy practices.
As predictive maintenance solutions provide facilities with deeper insights into the health of their refrigeration equipment, they have exposed flaws in their redundancy strategy. This article examines the risks of relying solely on N+1 redundancy and offers practical guidance for constructing more resilient and reliable storage systems.
Understanding N+1 redundancy
N+1 redundancy is a common strategy designed to ensure uninterrupted operation in the event of a chamber failure. Here’s how it works: if you have a room with five walk-in freezers in use (N=5), then you should have six freezers (5+1) always ready—five in use and one on standby as your backup. If one freezer fails, the products can be moved to the backup freezer. The outcome is less favorable if two freezers fail, which opens the door to increasing redundancy. For instance, N+2 redundancy would have two spare chambers for each set of assets, and 2N redundancy would have a spare chamber for each asset. Obviously, acquisition and operating costs, as well as the real estate footprint, increase substantially as redundancy levels increase, which is why N+1 is generally considered the sweet spot that balances cost with adequate safety and protection.
A successful redundancy strategy also includes spare components (such as compressors, evaporators, condensers, and control systems) to ensure that quick repairs can be made and to minimize dependency on any single component. Modern environmental chambers often have controllers that automatically switch between redundant components to balance the mechanical load or transfer it completely should one component fail.
The problem with N+1 redundancy
N+1 redundant practices are popular due to their simplicity, cost-effectiveness, and ability to meet regulatory requirements. They strike a balance between operational reliability and financial feasibility, making them an attractive option. Too often, however, it relies on narrowly scoped risk assessments, failing to account for the complex, real-world challenges that arise. While N+1 redundancy can provide adequate protection under ideal conditions, it falls short in practice—especially when monitoring systems focus too narrowly on a single variable.
Current good manufacturing processes (cGMP) require that the temperature inside a chamber be monitored. Yet if temperature is the only parameter tracked, emerging equipment problems may go unnoticed. For example, suppose one compressor fails, and the redundant one is automatically switched on. The chamber temperature will appear stable, giving no indication that redundancy has been lost.
This is a precarious situation because it creates a single point of failure that may not be immediately apparent to the maintenance team. As long as the lone compressor maintains the proper temperature in the chamber, there is no alert, and there is also no redundancy. Left unchecked, that lone compressor—which is now working overtime—will inevitably fail. Odds are it will fail outside of regular working hours. This means costly emergency repairs, product relocation, and, if no redundant chamber is available, loss of product.
Underestimating uncertainty
N+1 redundant systems are designed to tolerate only one failure, after which the system becomes vulnerable again. When multiple components fail simultaneously, or a cold storage facility experiences a cascading failure—where one fault triggers another—having only a single redundant component is not sufficient to protect the products.
Misguided reliance on N+1 redundancy alone assumes that the risks and conditions faced by cold storage facilities are static and predictable. This assumption is not only incorrect, but it also continues to have devastating consequences across the biopharma and life sciences industries, which lose billions of dollars per year to refrigeration failures.
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Cold storage facilities must continually adapt to uncertain conditions, including extreme weather, sudden power outages, and human error. Consider a walk-in chamber storing millions of dollars of biologics during an unexpected heatwave. The combination of increased ambient temperature and power fluctuations puts additional strain on the cooling systems, stressing them to their breaking point. This is a precarious situation that underscores the importance of having redundant systems at the ready, which will not be the case if those systems are already in use. This is where predictive maintenance practices come into play, ensuring that redundant assets and components are always available.
Predictive maintenance to the rescue
For redundancy to be reliable, two conditions have to be met. First and foremost, every primary chamber must be properly maintained to protect stored products. This reduces the likelihood of needing to use a redundant chamber. Secondly, every redundant chamber must also be maintained to ensure it is at the ready when needed. Accomplishing both of these requires that every critical component run optimally, which in turn requires capturing significantly more data both inside and outside the chamber. This is precisely what predictive maintenance delivers.
How predictive maintenance works
While every predictive maintenance solution has its own nuances, at the core, they utilize sensors to collect data from key refrigeration components and perform analytics on that data to quantify the overall health of a chamber. Obviously, the more parameters you monitor (temperature, pressure, electrical current, vibration, etc.) and the more powerful the analytics engine, the deeper the insights that can be achieved. A truly functional predictive maintenance system is capable of detecting the earliest indicators of a developing problem long before it actually manifests, enabling proactive repairs to be made.
Creating a successful redundancy strategy
A predictive maintenance system doesn’t replace a viable redundancy strategy; it ensures that those redundant systems are available when needed. In other words, using a predictive maintenance tool eliminates the core vulnerabilities of N+1 redundancy, transforming uncertainty into reliability.
Planning a redundancy strategy is actually quite simple—and executing on that strategy is where many facilities fall short. In general, you should have 10 percent redundant chambers (at a minimum), and optimally 20 percent. That means if a facility has 20 chambers, only 16-18 of them should be in use. The remaining chambers should be ready and maintained at the required temperature in case of an emergency. With that, the redundant chambers should mirror the primary chambers, meaning if you have 10 5°C chambers and 10 -40°C chambers in your facility, you should (ideally) allocate two redundant chambers of each type.
How to avoid common mistakes
Having a redundant chamber is like having a spare closet; it doesn’t remain “spare” for very long. When one or more chambers inevitably require emergency maintenance and products need to be moved, that is not the time to discover that the designated “redundant” chambers are already in use. Beyond the immediate chaos, there is the risk of costly product loss and CAPA documentation. To avoid this, it is essential that facility managers routinely take inventory of their chambers and physically confirm that at least 10-20 percent of their chambers are ready for emergency use.
Conclusion
The life sciences industry cannot afford to take risks with cold storage systems and the valuable products they store. Short of moving to fully redundant (2N) refrigeration systems, the future of cold storage lies in multilayered systems that support N+1 redundancy backed by early warnings from predictive maintenance solutions.
