Case Study: Automotive Supplier achieves predictive maintenance and reduced downtime with ifm efector

Automotive Supplier prevents $500,000 in downtime with ifm efector

An automotive supplier faced challenges with costly unplanned downtime and maintenance for their critical stamping presses. They partnered with ifm to implement a predictive maintenance solution using the moneo IIoT software platform to gain real-time insight into machine conditions and optimize their maintenance program.

ifm implemented a system using VSE vibration edge controllers and IO-Link sensors, which was installed and began trending data in just one day. This solution provided immediate results, including an alert that prevented an estimated $500,000 in maintenance costs and 5 weeks of downtime. The investment achieved an estimated return on investment in just 2.5 months, successfully transitioning the customer's maintenance from a preventative to a predictive schedule.