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Predictive Maintenance
Running a piece of equipment to the point of failure could cost 10 times as much as regular maintenance – so why should one do this? Application of predictive maintenance has risen from 47% to 51%, and due to this, failure of machines had dropped from 61% to 57% (see also) --- and predictive maintenance yields a tenfold return on investment, and it results in a savings of 30% to 40%.
So, what is Predictive Maintenance?
Predictive maintenance in fact, is the technology that exploit the presence of historical data of the asset and make the best use of them by training a machine learning module to be able to tell when an asset is going to fail ahead of time to prevent business interruption.
AIDirections’ Predictive Maintenance approach
Using AI, AIDirections has developed a predictive preventative maintenance solution to serve the following:
1-Preventing interruption of critical machinery
2- Establishing a low cost and efficient AI-based technology to prevent failures
To predict an equipment’s future state, a preliminary analysis and a framework needs to take place; this framework is based on:
1- involving data harvesting from already installed sensors;
2- applying 4 modules: condition monitoring, assessment, prediction, and maintenance planning.
If you wish to know more details, please look at our White Paper on Predictive Maintenance
Success Factors
There are several success factors for Predictive Maintenance projects:
1. Availability of all data needed for predictive maintenance over a given period
2. Reliable quality of the data retrieved and processed
3. Input from an experienced facility manager is available to set the parameters
4. Good level of data governance is needed to ensure data are ready and in place to be used
Interested in knowing more about AIDirections’ predictive maintenance? Please speak to us to schedule a demo.
So, what is Predictive Maintenance?
Predictive maintenance in fact, is the technology that exploit the presence of historical data of the asset and make the best use of them by training a machine learning module to be able to tell when an asset is going to fail ahead of time to prevent business interruption.
AIDirections’ Predictive Maintenance approach
Using AI, AIDirections has developed a predictive preventative maintenance solution to serve the following:
1-Preventing interruption of critical machinery
2- Establishing a low cost and efficient AI-based technology to prevent failures
To predict an equipment’s future state, a preliminary analysis and a framework needs to take place; this framework is based on:
1- involving data harvesting from already installed sensors;
2- applying 4 modules: condition monitoring, assessment, prediction, and maintenance planning.
If you wish to know more details, please look at our White Paper on Predictive Maintenance
Success Factors
There are several success factors for Predictive Maintenance projects:
1. Availability of all data needed for predictive maintenance over a given period
2. Reliable quality of the data retrieved and processed
3. Input from an experienced facility manager is available to set the parameters
4. Good level of data governance is needed to ensure data are ready and in place to be used
Interested in knowing more about AIDirections’ predictive maintenance? Please speak to us to schedule a demo.