Proactively Monitor Machine Health to Safeguard Your Science
Drawing on billions of data points generated every year for over a decade, Elemental Machines has developed an AI-prediction model to measure Freezer Health. This advanced tool tracks performance trends over time and identifies key cross-over points to predict the likelihood of freezer failures and the need for preventive maintenance. Beyond alerting, the machine learning algorithms are specific to -20°F and -80°F and even unique brand signatures to ensure your assets are safe and enabling you to avoid emergencies by providing “early warning” signs.
Advanced AI-Predicted Health Score Algorithm
Our proprietary AI-Predicted Health Score algorithm leverages machine learning to analyze continuous data streams from laboratory freezers, focusing on critical metrics such as power usage and temperature fluctuations. By comparing these data points against models of ideal freezer operation, the Health Score can detect deviations that indicate potential issues:
Technical Insight Into Freezer Performance
At the core of the AI-Predicted Freezer Health Score solution is a deep analysis of thermo-power dynamics, which helps discern the operational integrity of the freezer without being misled by temporary fluctuations like door openings. Our highly refined solution gives you exactly the information you need, and nothing you don’t:
Avoid Catastrophes; Predict Freezer Failures
The AI-Predicted Health Score provides real-time performance trends so you can monitor the health of your most crucial samples. Install in less than 5 minutes and within days, a freezer-specific prediction model can track minute changes in freezer mechanical performance. Although it might seem like freezers fail “instantly,” there are actually subtle variations and events that can be detected with AI to predict the probability of freezer failures and can indicate that preventive maintenance may be necessary. Beyond reporting, Elemental Machines’ emergency monitoring services will let you know as soon as your equipment crosses into the “Red Zone,” allowing you to take immediate actions to secure your scientific assets.
Evolution of an AI-Driven Prediction of Freezer Health
Elemental Machines has monitored the assets of a Top 15 Pharma company for over 5 years. As a “proof of concept,” the company asked us to use the Freezer Health algorithm to retroactively identify which freezers would have failed. We correctly identified all of the failed freezers in the sample dataset, plus a few more that required maintenance.
On the strength of that assessment, we began rolling out Freezer Health in multiple locations, and within days, the algorithm detected an impending freezer failure allowing the company to preventively move samples and fix the freezer. We can do the same for your critical scientific samples.