Case Study: GEBHARDT Fördertechnik achieves predictive maintenance in warehouse automation with Crosser

GEBHARDT Fördertechnik - Customer Case Study

GEBHARDT Fördertechnik, a company specializing in warehouse automation systems, faced the challenge of minimizing maintenance costs for its shuttle systems, which experienced problematic vibrations during operation. The company wanted to detect anomalies, perform root cause analysis, and use this data to feed AI models for predictive maintenance. To tackle this, they partnered with Crosser and utilized its Crosser Edge Node and Crosser Cloud services.

The solution implemented by Crosser enabled GEBHARDT to process sensor data directly at the edge in real-time, harmonizing and enriching it before sending only relevant information to the cloud. This Crosser system provided the data foundation for predictive maintenance models, allowing GEBHARDT to move from rigid maintenance intervals to flexible schedules. The results included increased machine availability, extended machine lifetime, and significant cost savings on cloud storage and interfaces due to the edge data processing.

GEBHARDT Fördertechnik

Marco Gebhardt

CEO