Systems operating in industrial settings require a high degree of Reliability and Availability. Facilities like power generation plants, manufacturing lines, and oil & gas drilling sites rely on the operational capability of complex equipment.
The consequences of unscheduled maintenance include not just the costs of lost production revenue. Failures impact the bottom line through repair and clean-up costs while critical failures can potentially cause harm to people and the environment. Reducing the likelihood of failure in these environments has long been a goal of Reliability Engineering.
This session will discuss Machine Learning analysis, how it will better identify failures and improve preventative maintenance while providing an example of a real world application of the process.