Why do you have to do predictive maintenance?
Existing maintenance models have shown some limits. On the one hand, corrective maintenance makes you wait for a failure before repairing. On the other hand, preventive maintenance often schedules maintenance programs too early whereas the machine could be used a few weeks more.
Predictive maintenance enables companies to preempt failure by collecting data from various sources (sensors, IOT, GMAO) in order to make correlations between them and find failure patterns.
The aim of predictive maintenance? To act just before the failure happens and stop the equipment. It is important to determine the right moment by getting the right people, the accurate material, and so on.
How Saagie helps?
Saagie is a Big Data full stack platform which enables you to define a predictive maintenance strategy of a various kind of equipment: automatons, candelabras, interactive billboards, traffic signals.
The platform will help you to define a data pipeline in order to assist your predictive maintenance platform from data extraction to accurate creation of failure patterns.
How ? The main steps of the project
Collection of all the data of the company and storage in a data lake. IoT, sensors and data from GMAO with all failure background, including preventive or or corrective operations.
Data analysis by the Data Scientists in order to create a basis for learning..
Detection of failure and operations patterns.
Bouygues has opted for predictive maintenance (video)
What are the benefits?
With production systems analysis, predictive maintenance allows you to: