Predictive & Preventive Maintenance Training

Training courses in electric motor and generator repair and mainentance
IPS conducts training courses across the country,
featuring industry-leading experts in electric motor
and generator diagnostics, maintenance and repair.


PdMA testing, a key part of a cost-effective
preventive maintenance program.

Your electric assets are critical to your plant’s operating efficiency and reliability, but chances are they’re overdriven and prone to failure. Our AC & DC Electric Motor Training Courses will show you how to maintain rotating assets at peak operating efficiency, giving you the tools you need to lower your maintenance costs and increase reliability.

Each two-day, high-intensity course, taught by leading industry experts, takes you inside AC and DC machines. You learn how they run, what environmental and operating conditions do to electrical and mechanical components, and how to recognize early-stage problems — before they lead to motor failure.

Understanding your rotating assets is critical to getting more out of them. It also helps you work more effectively with your power services provider, whether you’re working within a planned outage or responding to an emergency.

If you’re ready to move from a repair-focused stancewith its unplanned downtime, emergency costs and low reliability — to the cost efficiency and uptime of a predictive maintenance-based program, then the first step is the IPS AC & DC Electric Motor Training Courses. To learn more, call your regional IPS sales representative or email us.

 

  • For electricians, technicians and maintenance personnel
  • High-intensity curriculum covers operating theory, testing
    and maintenance for AC and DC motors and generators
  • Taught by industry-leading experts
  • Learn how to identify motor construction, components and applications
  • Learn how to recognize early-stage operating problems and develop action plans
  • Develop a better understanding of predictive and preventive services
  • Move toward the cost efficiency and uptime of a predictive maintenance-based operation