DevOps with MATLAB: A Predictive Maintenance System for Streaming Data

Overview

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 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 webinar, we will demonstrate a complete predictive maintenance DevOps system for monitoring the state of health (SOH) of a battery fleet. You’ll first learn how to develop an SOH prediction model and a drift detection model in MATLAB. Then, we’ll show 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.

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

About the Presenters

Christine Bolliger is a senior application engineer at MathWorks supporting Swiss customers across different industries in the areas of software engineering, data science and cloud computing. Before joining MathWorks, she worked as a software engineer and leader of a data science team. She holds master's degrees in Physics and Computational Science & Engineering from the University of Bern and ETH Zurich and has a PhD in Biomedical Sciences.

Nicole Bonfatti is a product marketing manager focused on application deployment with MATLAB Production Server with over 10 years of experience at MathWorks. They have additional experience incorporating deep learning models into both embedded systems as well as web services at an AI startup. They hold a BS in Computer Science, an MS in Management of Technology combined with an AWS Solution Architect certification.

Seth DeLand is a product marketing manager for MATLAB AI products. Prior to that, he was product marketing manager for MATLAB optimization products. He earned his B.S. and M.S. in mechanical engineering from Michigan Technological University.