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Smart Maintenance

Starter-kit for smarter maintenance

Manufacturing processes generate large amount of data, but only few organization collect this data and even fewer are able to exploit it. Predictive maintenance is about using data, for determining when a device should be maintained based on its actual maintenance needs. This means moving from a year- or calendar based maintenance system to a process where actions are taken when there is a real need for them. Predictive maintenance can decrease critical downtimes and make the resource planning more efficient. Besides maintenance and repair resources can easily be allocated where they are needed the most which leads to higher performance.

EXPLORE what we know and do
EXPLORE what we know and do

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Competence areas

Several manufacturing companies have recognized the possibilities of product line data collection, but they just do not know how to get started. Enfo’s Smart Maintenance starter kit contains general sensors that enable monitoring of product line operations such as temperature, sound and fibrillation. Industrial PC that is included to the package prepare the sensor data and send it to cloud for storage and analyze by using mobile data included in the package. Everything needed is packaged to one compact kit, so the solution is up and running very quickly.

In the first phase the scope of the starter-kit project is carefully defined with a customer, in order to achieve results in an agreed time frame. Smart Maintenance is a cost efficient low-threshold solution that helps you to get started with production line data collection that is key to predictive maintenance and quality improvement solutions. Only in few short weeks, we will be able to provide you concrete results and guidelines on how to move forward.    

In addition to data collection, data refinement and data combine from different sources are also key elements needed to succeed. This is where we at  Enfo are at our best, since we have a comprehensive knowhow about data system integrations and data source combining. When we add predictive analytics and machine learning, on top of that we have a solution that can perceive completely new causal connections.