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Predictive Maintenance
Reduce production downtime due to breakdowns with Machine Learning and AI
Predictive Maintenance
Reduce Production Downtime Due to Breakdowns with Machine Learning and AI
At Becolve Digital, we are transforming the way companies manage their production equipment by using Machine Learning and Artificial Intelligence to detect anomalies and breakdowns before they occur, enabling more efficient maintenance and reducing production costs. Discover how you can take your industry to the next level with a predictive maintenance solution.
Did You Know…?
According to a study by ARC Advisory Group, only 18% of asset failures are related to the “aging” of the assets and can be prevented with preventive maintenance programs.
That is, to prevent the remaining 82% of asset failures, predictive technology is required.
Source: ARC Advisory Group
Maintenance Strategies to Predict Breakdowns
There are mainly two maintenance strategies that allow predicting and anticipating failures and breakdowns: Condition-Based Maintenance and Predictive Maintenance.
Condition-Based Maintenance (CBM) is applied when the condition to be monitored is known and definable by a rule-based logic. These rules must be fixed over time and do not change depending on load, environmental, or operational conditions.
Predictive Maintenance is applicable when asset modeling based on rules is too complex or the specific rules for monitoring the health and/or performance of assets are not explicitly known. It is also applicable when the rules vary according to load, environmental, or operational conditions.
What is Predictive Maintenance?
Predictive maintenance is an advanced technique that uses real-time data and intelligent analysis to anticipate failures and breakdowns in industrial equipment before they occur. These predictive maintenance 4.0 solutions collect relevant data from your production equipment and use Machine Learning and Artificial Intelligence algorithms to identify patterns and anomalies that may indicate potential future breakdowns.
Advantages of Predictive Maintenance
- Improved operational efficiency: Optimizes equipment performance, reducing downtime and maximizing its lifespan.
- Cost reduction: Detecting and resolving problems before they become major breakdowns avoids costly shutdowns and production losses.
- Improved safety: Ensures a safer environment for workers by minimizing the risk of accidents related to equipment failures.
- Strategic planning: Knowing in advance when maintenance is necessary allows you to schedule it more effectively, avoiding unforeseen interruptions in production.
- Increased lifespan: By performing precise interventions at the right time, you extend the lifespan of the equipment and maximize the investment.
How does it work?
- Historical data collection:
Capturing historical data from the equipment to be monitored for processing and cleaning. - Creation of the model with Machine Learning:
Using powerful Machine Learning algorithms to analyze the collected data and, through advanced pattern recognition, create the predictive model. - Real-time monitoring:
Using AI, a comparison is made between the real-time data of the asset and the predictions of the model. - Detection of anomalies and potential breakdowns:
Based on data analysis, AI identifies anomalies and potential future problems in the monitored equipment. - Real-time alerts and notifications:
Issuing instant alerts by email, informing about any potential problem that requires attention. - Failure diagnosis:
AI is responsible for analyzing the deviation patterns of the asset and diagnosing the possible causes of the deviation, providing a preliminary diagnosis for further detailed analysis. - Prescriptive Maintenance:
Once the failure has been diagnosed, the system reports the following operational and maintenance actions to be carried out for its correction. - Rest Usefull Life Estimation (RULE):
The system’s algorithms are responsible for estimating when the breakdown or failure will occur based on the data collected in the last hours or days. - Model retraining:
In the event that it is a false alarm generated by load, operational, or environmental conditions not known by the model, it can be easily retrained with the data that defines the new conditions. - Intuitive reports and visualizations:
Access detailed reports and clear visualizations that will help you understand the performance of your equipment and make informed decisions.
Trust the Experience and Technology of Becolve Digital
Our team of experts in Machine Learning and Artificial Intelligence is dedicated to providing you with high-quality, customized predictive maintenance solutions for your industry. By combining our experience with cutting-edge technology, we are ready to take your company towards a more efficient, safe, and profitable future.
Do not waste any more time with corrective maintenance! Join us today and take your industry to the next level!
Contact us now for a free demonstration and discover how we can improve the efficiency of your industry with our predictive maintenance system based on Machine Learning and Artificial Intelligence.
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