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Deploy Predictive Maintenance Algorithms

Implement and deploy condition-monitoring and predictive-maintenance algorithms

Deployment or integration of a predictive maintenance algorithm is typically the final stage of the algorithm-development workflow. How you ultimately deploy the algorithm can also be a consideration in earlier stages of algorithm design. MathWorks® products support several phases of the process for developing, deploying, and validation process for predictive-maintenance algorithms.


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codegenGenerate C/C++ code from MATLAB code
mccCompile MATLAB functions for deployment
saveRULModelForCoderSave RUL model for use in code generation
loadRULModelForCoderLoad and reconstruct RUL model from file for use in code generation
readStateGet degradation RUL model state for use at runtime
restoreStateRestore degradation RUL model state at runtime


Deployment Basics

Deploy Predictive Maintenance Algorithms

Understand the phases of deployment and implementation of your predictive-maintenance algorithm.

Deploy RUL Prediction Algorithms

Generate Code for Predicting Remaining Useful Life

Deploy an algorithm for predicting remaining useful life (RUL). Such code generation is useful when you have trained an RUL model and are ready to deploy the prediction algorithm to another environment.

Generate Code that Preserves RUL Model State for System Restart

Generate code that preserves the state of the RUL model when the prediction algorithm is stopped and restarted.