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This video explains different maintenance strategies and walks you through a workflow for developing a predictive maintenance algorithm.
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.
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.
Learn about different maintenance strategies and predictive maintenance workflow:
- MATLAB and Simulink for Predictive Maintenance: bit.ly/2Tp2yLq
- Designing Algorithms for Condition Monitoring and Predictive Maintenance: bit.ly/2GsiGae
- Using Simulink to Generate Fault Data: bit.ly/2Gnb7Bw
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