Controlled maintenance,
anticipation of results
Prevention of Incidents and Costly Failures
One of the most valuable applications of Teal Neural is its ability to prevent failures before they occur. Through constant monitoring and detailed analysis of operating conditions, Teal Neural can identify subtle changes and patterns that may indicate an emerging issue.
Temperature control is a key example. Unusual variations in temperature can be an early indicator of malfunction or an impending failure. By continuously monitoring equipment temperature, Teal Neural can alert operators to these changes, allowing them to investigate and address the issue before it causes a failure.


This has multiple benefits. First, it can prevent unplanned downtime that disrupts production and can lead to costly delays. Second, it can prevent more serious equipment damage that can be expensive to repair and, in the worst case, may require equipment replacement. Lastly, by identifying and addressing issues early, potential safety incidents that could endanger personnel can be avoided.
Using Teal Neural for monitoring and incident prevention not only improves efficiency and safety but can also have a positive impact on the company’s financial performance. The cost savings from avoided repairs, replacements, and downtime can be significant, and these savings can be reinvested in other areas of the company.
Preventive Maintenance
Maintenance Forecast
Equipment preventive maintenance is a critical aspect of ensuring the efficiency and longevity of any production infrastructure. Thanks to Teal Neural, companies can transform their maintenance approach from reactive to proactive.
Utilising its deep learning and pattern analysis capabilities, Teal Neural continuously monitors the state and performance of machines over time. This constant monitoring, combined with its ability to analyse historical data and detect patterns, allows the system to predict when a machine is likely to need maintenance before a problem arises.
These predictions are valuable for several reasons: