Many legacy maintenance teams are thinly staffed, lack thermal domain expertise, and have gotten very good at reacting to rising unplanned downtime incidents. In touch times, this culture is driving many companies to the brink of failure.

The advent of low-cost wireless technologies, asset historians, and analytics models are driving the industry towards a future of automated predictive maintenance programs that will increase asset reliability, shorten maintenance times, boost safety and quality, reduce maintenance costs, and much more.

This session will discuss the use of Big Data, the Internet of Things, and Predictive Analytics to improve thermal equipment reliability and reduce maintenance costs.

Join Dale Smith for this 60-minute webinar to review reliability, maintenance, and operations successes and lessons by analyzing data to drive actionable intelligence.

• Thermal Process Failure Modes

• Balancing the Reliability and Safety Model

• Deep Dive with Thermal Analytics

• Visual Data Exploration / Dashboards

• Use Cases for Predictive Technologies / Maintenance.