Predictive Maintenance

MATLAB and Simulink for Predictive Maintenance

Develop and deploy custom predictive maintenance algorithms

Empower Your Engineers

MATLAB is the easiest most productive environment for engineers to develop predictive maintenance algorithms and deploy them in operation.

Design Predictive Algorithms

Detect anomalies, identify faults, and estimate remaining useful life with domain-specific features and low-code AI

Model Components and Systems

Reuse models from design, generate synthetic sensor data, build and integrate digital twins

Deploy Anywhere

Integrate with IT/OT systems in the cloud, or generate C/C++ code for real-time processing

Design Predictive Algorithms

Creating a reliable predictive algorithm is more than just AI: access, clean, and explore your data, then use your engineering expertise to extract the best features for training predictive algorithms. Get started quickly with application-specific functions and reference examples.

  • Access streaming and archived data using built-in interfaces to cloud storage, databases, data historians, and industrial protocols
  • Clean and explore data using interactive statistical and signal processing techniques
  • Extract and rank time-domain, frequency-domain, and application-specific features with the Diagnostic Feature Designer
  • Identify faults and predict time-to-failure using low-code AI, statistical, and model-based methods

Model Components and Systems

With physics-based models built in Simulink and Simscape, you can generate synthetic fault and degradation data, identify the best sensors, and simulate future performance.

  • Create or repurpose Simulink and Simscape models of components and systems
  • Tune model parameters to match real equipment performance
  • Generate synthetic fault and degradation data for training predictive algorithms
  • Deploy models as digital twins

Deploy Anywhere

Shorten response times, transmit less data, and make results immediately available to operators by implementing your MATLAB algorithms on embedded devices and in enterprise IT/OT systems.

  • Eliminate hand-coding by generating C/C++ code from MATLAB for real-time processing directly on assets and edge devices
  • Scale your MATLAB algorithms by integrating with a variety of cloud platforms—without recoding or creating custom infrastructure

Want to discuss Predictive Maintenance for your organization?

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