Improving Predictive Maintenance for Manufacturers with Data + AI

Maintaining equipment on a shop floor, in a fleet or in the field is a complex endeavor for most companies. Each piece of equipment can generate terabytes of unstructured and semistructured data each day and be located around the globe and in the sky.

Knowing when equipment needs maintenance is critical to companies. Unplanned downtime is a major disruption to our businesses. A failure of a key component can cost millions of dollars of lost production per day in addition to downstream impacts to production and customer agreements. An important way to save time and money is to use machine learning to better predict outages earlier and plan maintenance work before the failure occurs.

In this session, Databricks Global Manufacturing and Logistics Leader, Rob Saker, will lead an in-depth discussion on how manufacturers are transforming their business with data and AI, taking advantage of internal and external data sources across a range of unstructured, semistructured and structured data to deliver insights in near real-time.

Rob will be joined by a Databricks solution architect who will walk through how to build a real-time end-to-end data pipeline from the IoT device with streaming ingestion for any structure of data, and use Databricks ML to predict specific component failures against these data sets to ensure greater quality, efficiency and availability. And we will walk through our free Predictive Maintenance Solution Accelerator that you can use following the webinar to start improving predictive maintenance inside your organization.

Agenda at a glance

• Introduction to Data + AI in Industry 4.0
• IoT Predictive Maintenance
• Q&A