Service Agreements for MAAG® Gear Units

Key Benefits

• Increase productivity and reliability
• Bespoke service agreements, tailored to your needs
• Supports and predictive maintenance approach
• Reduce OPEX

Service agreements for MAAG gear units

Gear unit failure can be incredibly disruptive to your process. But with a predictive maintenance approach, you can avoid failure altogether and, instead, make the most of all your scheduled downtime. The agreements provide the tools and expert support to carry out the right maintenance at the right time, every time.

What We Offer

Tailored service agreements that help you optimise gear performance

The gear unit is the link between the drive and driven machine – if it fails, everything stops. That’s why getting on top of maintenance activities is so important. But gear units and their maintenance requirements are as individual as the applications and operation, so one-size-fits-all maintenance plans aren’t sufficient.

Working in combination with MAAG Predicta online condition monitoring services, these modular service agreements are designed to ensure you achieve the highest overall equipment efficiency – and maximum productivity.

How does it work?
Five basic questions help you define the perfect service module for your equipment:

• Does a breakdown of the gear box lead to immediate production losses?
• How does the cost of repair compare to the cost of replacement?
• Is the equipment easy to replace ?
• Does the equipment have a long lead time ?
• Does the equipment require advanced maintenance knowledge?

Together with you, the service team analyses the strategic importance of the gear unit and determine its influence on the driven equipment’s overall reliability. After all, it makes sense to spend less effort maintaining gears that are quick and cheap to replace. Depending on the importance of the equipment, the service contract includes one-off expenses for hardware and the installation of online condition monitoring, as well as periodic costs for on-site inspections and continuous monitoring and data analysis.