AI-Powered Electrical Asset Condition Monitoring: The Future is now
As technology continues to advance, more and more industries are turning to artificial intelligence (AI) to improve their operations. One area where AI is making a significant impact is in electrical asset condition monitoring. In this post, we’ll take a closer look at the benefits of using AI-based systems for monitoring the condition of electrical assets.
Improved Equipment Reliability
One of the key benefits of using AI-based systems for electrical asset condition monitoring is improved equipment reliability. These systems use a combination of machine learning algorithms and sensor data to continuously monitor the condition of electrical assets. If an issue is detected, the system will alert maintenance teams, who can then perform repairs before a failure occurs. By catching issues early on, AI-based systems can help to increase the overall reliability of equipment and reduce the risk of unexpected failures.
Another benefit of using AI-based systems for electrical asset condition monitoring is reduced downtime. By identifying and addressing issues before they cause equipment failure, these systems can help to minimise disruptions to operations. This can help to increase overall plant availability and ensure that production is able to continue smoothly.
AI-based systems are also able to analyse large amounts of data in real-time, which can lead to more accurate and efficient decision-making when it comes to maintenance and repair. With the help of machine learning algorithms, these systems can identify patterns and trends in sensor data that might not be immediately obvious to human operators. This can help to improve overall efficiency and reduce the need for manual monitoring and analysis.
Better prediction and preventions of failures
One of the most important aspects of AI-based systems is the ability to predict which equipment is more likely to fail. With large amounts of data, AI can make predictions on the failure rate of equipment, and with that it’s possible to plan preventions and maintenance. This will help to avoid unexpected failures, and decrease downtime.
Finally, one of the most tangible benefits of using AI-based systems for electrical asset condition monitoring is cost savings. By reducing the frequency and duration of equipment failures, these systems can help to lower maintenance costs. Additionally, by improving overall plant efficiency, AI-based systems can help to reduce operating costs and improve the bottom line.
Numen AI asset monitoring system
Numen has been specifically developed by Ecocentric Energy to be a cost-effective, non-intrusive and easy to deploy, data acquisition and analysis platform that makes AI-based condition monitoring of electrical assets a reality in many commercial and industrial environments.
In addition to the benefits of asset condition monitoring, Numen makes detailed electrical data available to users via a modern web interface and application programming interface (API) which further drives energy efficiency and data driven decision making.
In conclusion, AI-based electrical asset condition monitoring is an innovative and effective way to ensure the reliability of equipment, reduce downtime, improve efficiency, predict equipment failures and prevent them, and ultimately save cost. With the help of machine learning and sensor data, companies can use AI-based systems to gain a deeper understanding of the condition of their electrical assets and make informed decisions about maintenance and repair.