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Exhibitor & products of the SPS 2025

MathWorks

Predictive Maintenance Toolbox

Predictive Maintenance Toolbox

Description

Predictive Maintenance Toolbox™ lets you manage sensor data, design condition indicators, and estimate the remaining useful life (RUL) of a machine.

The toolbox provides functions and an interactive app for exploring, extracting, and ranking features using data-based and model-based techniques, including statistical, spectral, and time-series analysis. You can monitor the health of batteries, motors, gearboxes, and other machines by extracting features from sensor data. To estimate a machine's time to failure, you can use survival, similarity, and trend-based models to predict the RUL.

You can organize and analyze sensor data imported from local files, cloud storage, and distributed file systems. You can label simulated failure data generated from Simulink models. The toolbox includes reference examples for motors, gearboxes, batteries, pumps, bearings, and other machines that can be reused for developing custom predictive maintenance and condition monitoring algorithms.

To operationalize your algorithms, you can generate C/C++ code for deployment to the edge or create a production application for deployment to the cloud.

More products by MathWorks

Simulink

Simulink® is a block diagram environment used to design systems with multidomain models, simulate before moving to hardware, and deploy without writing code.

Simulink is used for control systems design, electrification, robotics and autonomous systems, digital twins, and artificial intelligence.

In Industrial Automation and Machinery, Simulink is used for creating virtual models to simulate and test systems early and often, to validate designs through Hardware-in-the-Loop and rapid prototyping, and to generate production-quality C, C++, IEC 61131, Verilog and VHDL code.

Some highlights of using Simulink include:

  • Model-Based Design: To transform development of complex systems, market-leading companies adopt Model-Based Design by systematically using models throughout the entire process.
  • Simulation: Explore a wide design space and test your systems early with multidomain modeling and simulation.
  • Model-Based Systems Engineering: Model-based systems engineering (MBSE) is the application of models to support the full system lifecycle. Simulink bridges development from requirements and system architecture to detailed component design, implementation, and testing.
  • Agile Software Development: Agile software development helps teams deliver value to their customers faster using short iteration cycles with an emphasis on continuous integration and team collaboration. Simulation, automated testing, and code generation shorten the development cycle, enabling you to become a successful Agile team.