What do you expect from predictive maintenance?

• Maintenance cares about day-to-day operations – Reduced downtime
• Operations and IT look at the bigger picture – Improved operating efficiency
• Engineering groups get product feedback – Better customer experience
• Upper management wants to drive growth – New revenue streams

Why MATLAB and Simulink for predictive maintenance?

• Get started quickly
• Reduce the amount of data you need to store and transmit
• Deliver the results of your analytics based on your audience
• Create training data for your algorithm in the absence of real failure data

You can watch Branko’s full talk and download related resources from MathWorks Videos and Webinars.

You might have noticed recently on ThingSpeak that you can link your ThingSpeak user account to a MathWorks Account. By doing so, you have access to other MathWorks products and services that you can use with the same user account. MATLAB Mobile is a native Apple or Android app that allows you to evaluate MATLAB commands, create and edit files, view results, acquire data from sensors, and visualize data. MATLAB Mobile also has thingSpeakRead and thingSpeakWrite functions built-in. One exciting aspects of MATLAB Mobile is that you can capture the sensor data of the mobile device and send it to MATLAB Online.

To take the project further, you can use additional toolboxes from MathWorks to preprocess the data and do advanced mapping. Takuji demonstrates using the Signal Processing Toolbox to filter, down sample, and remove outliers from the incoming data from the MATLAB Mobile sensors. Using the Mapping Toolbox, he plots the latitude and longitude of his mobile device on a WPS map and displays the map on a ThingSpeak channel.

Takuji has shared all of the source code and steps on File Exchange so you can replicate this project on your own mobile device. Check out his project on File Exchange and see his raw data and visualizations on ThingSpeak.