Predictive maintenance is a key initiative and a strategy that directly impacts the bottom lines of many industrial operations around the globe. Yet many of the organizations don’t know where and how to start due to a lack of knowledge about data platforms, methodology, and analytics techniques. Based on the recently released “Splunk Essentials for Predictive Maintenance” app that offers key methodologies and Splunk’s powerful machine learning capability, this session will demystify the data science elements of predictive maintenance to make the process real and pragmatic. Through this session, the audience will learn and appreciate the power of Splunk in a way that will allow agile application of analytic-driven predictive maintenance to the broader moving parts of their operations.

Speaker(s)
Young Cho, Senior IoT Practitioner, Splunk

Slides PDF link - https://conf.splunk.com/files/2019/slides/IoT1103.pdf?podcast=1577146205

Product: Splunk Enterprise, Splunk Machine Learning Toolkit, AI/ML

Track: Internet of Things

Level: Intermediate