DevOps with MATLAB: A Predictive Maintenance System for Streaming Data

Many organizations use MATLAB^® and Simulink^® to develop algorithms—but how do they deploy, monitor, and manage them over their lifetime? DevOps refers to the set of capabilities, tools, and best practices needed to operationalize software applications, usually in an IT context. But Gartner reports that more than 50% of data science projects do not result in business value due to difficulties with operationalization.

In this session, see a demonstration of a complete predictive maintenance DevOps system for monitoring the state of health (SOH) of a battery fleet. Learn how to develop an SOH prediction model and a drift detection model in MATLAB. Then, see how to automatically test and deploy these algorithms in operation using a CI/CD pipeline, MATLAB Production Server™ on Microsoft Azure^®, and dashboards for performance monitoring.

Discover how engineering teams can use MATLAB to operationalize their algorithms and how to bridge the gap with IT/OT teams.