Industrial Predictive Maintenance

Detect anomalies by analyzing data and predict future industrial equipment failures before they happen.

Automation of predictive maintenance

The implementation of a predictive maintenance system enables the anticipation of a failure or an incident in industrial machines by analyzing the data of their operation, whereby a possible performance degradation is detected in time before it occurs. A large amount of data history, both of correct operation and of failures, is typically required to train the models that detect these anomalies. However, this solution developed by Keepler removes this barrier and can work with a reduced data set and current data of correct operation.

For those companies that want to improve their service and save costs, this is a cloud-based solution that relies on machine learning in order to continuously optimize the predictive algorithm. Fully customizable to give the best answer to performance and maintenance issues.

Monitor and acts according to the data
  • If your infrastructure and machinery are sensor-equipped, you can know about their performance and status even in real time, which can be the starting point for your predictive maintenance strategy.
  • The extraction and configuration of records that require a limited amount of historical (non-erroneous) and current operational data.
  • All the information ingested feeds the data model in the cloud, where it is retrained to improve the reliability and accuracy of the predictions.
  • The dashboard view enables the configuration and management of alarms and the display of information.
We give you reasons to entrust maintenance to Artificial Intelligence

Rely on an A.I and cloud-based solution that combines the benefits of the cloud and the advantage of preventive maintenance.

Cost savings

Preventing errors plays a central role to avoid costs incured in system downtimes or replacement of machinery. The cloud approach enables pay-per-use instead of licence models.

Service improvement

Avoid system failures and prolonged downtimes, in favor of a better service and greater system efficiency . For this purpose, configuration and customization of appropriate alarms to each system are the key tool.

Increase in the useful life

Proper maintenance lengthens the life of machinery. Compared to the systematic routine time-based maintenance model, predictive maintenance has the advantage that in most cases no major repairs have to be carried out.

Learn from your own data

There is no need for a large amount of previous data. It enables the analysis of behavior patterns from a small data set of historical data and data of the current status.

Accelerates time-to-market

It deploys an architecture up to 75% faster than a solution that starts from scratch, but retains all the advantages of customization and individual configuration in data analysis.

Would you like to know how AI will improve the maintenance of your industrial machinery?

Contact us and we will start working together.

  • We’ll talk to you to determine your specific needs and the infrastructure of the devices you already have.

  • We will make you a proposal with a technological and business strategy so that you get results in the shortest possible time.

  • We start to work, always in coordination with your team, in order to have an MVP in a few weeks, and develop from there.

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