Getting Started with Predictive Maintenance
This video explains different maintenance strategies and walks you through a workflow for developing a predictive maintenance algorithm.
- Overcoming Four Common Obstacles to Predictive Maintenance: http://bit.ly/2GoZjyI
- MATLAB and Simulink for Predictive Maintenance: http://bit.ly/2E5LRgh
Predictive maintenance lets you find the optimum time to schedule maintenance by estimating time to failure. It also pinpoints problems in your machinery and helps you identify the parts that need to be fixed. Using predictive maintenance, you can minimize downtime and maximize equipment lifetime.
- Designing Algorithms for Condition Monitoring and Predictive Maintenance: http://bit.ly/2GsiGae
- Using Simulink to Generate Fault Data: http://bit.ly/2Gnb7Bw
This video uses a triplex pump example to walk you through the predictive maintenance algorithm steps. To develop an algorithm, you need a large set of sensor data collected under different operating conditions. In cases, where sensor data is not enough, you can use simulation data that is representative of failures by creating a model of your machine and simulating faulty operating conditions. For more information on generating failure data using Simulink®, please check out the links given below.
Get a free product Trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See What's new in MATLAB and Simulink: https://goo.gl/pgGtod
© 2018 The MathWorks, Inc. MATLAB and Simulink are registered
trademarks of The MathWorks, Inc.
See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
This video explains different maintenance strategies and walks you through a workflow for developing a predictive maintenance algorithm.
– Overcoming Four Common Obstacles to Predictive Maintenance: http://bit.ly/2GoZjyI
– MATLAB and Simulink for Predictive Maintenance: http://bit.ly/2E5LRgh
Predictive maintenance lets you find the optimum time to schedule maintenance by estimating time to failure. It also pinpoints problems in your machinery and helps you identify the parts that need to be fixed. Using predictive maintenance, you can minimize downtime and maximize equipment lifetime.
– Designing Algorithms for Condition Monitoring and Predictive Maintenance: http://bit.ly/2GsiGae
– Using Simulink to Generate Fault Data: http://bit.ly/2Gnb7Bw
This video uses a triplex pump example to walk you through the predictive maintenance algorithm steps. To develop an algorithm, you need a large set of sensor data collected under different operating conditions. In cases, where sensor data is not enough, you can use simulation data that is representative of failures by creating a model of your machine and simulating faulty operating conditions. For more information on generating failure data using Simulink®, please check out the links given below.
Get a free product Trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See What’s new in MATLAB and Simulink: https://goo.gl/pgGtod
© 2018 The MathWorks, Inc. MATLAB and Simulink are registered
trademarks of The MathWorks, Inc.
See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
