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 pre-empt 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.
The advantages of predictive maintenance?
With production systems analysis, predictive maintenance allows you to :
- Predict failures before they happen
- Minimize the costs due to engine repair
- Reduce machines downtime
- Optimize material and human resources
- Improve energy efficiency
Bouygues has opted for predictive maintenance (video)
Saagie helps you to implement predictive maintenance projects
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.