This is the fourth of a four-part video series.
Part 1: Predictive Maintenance in a Digital Age
Part 2: Developing AI Predictive Maintenance Models
Part 3: Make the Most of AI During Deployment
Machines tend to break down on their own schedule, but there usually are warning signs before a catastrophic failure. Improved sensors and software have pointed to a new way to measure, manage and maintain a machine’s health so that problems can be identified before they actually occur.
The idea of preventive maintenance has been around for years, but with the increased demands on manufacturing, maintaining machine uptime has pointed operations and maintenance teams toward the value of predictive maintenance as a potential profit center instead of a cost center.
In the fourth part of our series, Machine Design spoke with Philipp Wallner, the industrial manager for medical devices, industrial automation and machinery and utilities and energy at MathWorks to look at how predictive maintenance has evolved and where it might next be headed.
