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Last year US industry spent over $600 billion on plant and equipment maintenance. According to industry experts, at least $200 billion was wasted. Other industry statistics suggest that 80% of all failures of plant and equipment occur on a random basis and only 20% of the failures are age related. This means that 80% of failures have not been detected with common test and maintenance practices and therefore have not been prevented. Can the situation be improved?

With the cost of downtime in a large integrated pulp & paper mill ringing in at over $50,000/hour, historic methods to prevent downtime involve time based preventive maintenance practices or scheduled outages. Although this method of maintenance is available at a lower cost than downtime, it is still very expensive and often times ineffective. Preventive maintenance is invasive by design and can sometimes end up being the cause of premature equipment failure. Over 40% of the time that a needed part is identified during a scheduled outage, it is found to not be readily available. The Forest Products Industry is quickly moving toward predictive diagnostic methods. This approach assures that uptime is maximized at the lowest possible cost. Because this approach is non-invasive in nature, the plant can continue to run efficiently while critical components of the system are being checked for reliability and integrity. Facility electrical maintenance is able to diagnose potential problems in advance, while minimizing exposure to potential arc-flash hazards typically encountered during scheduled outages.

Eaton offers leading technology solutions to drive today's industry toward a more efficient and cost effective predictive maintenance model. Recent installations of Eaton Intelligent Technologies™ DeviceNet Motor Control Centers have changed the tools used by our customer's maintenance electricians from a volt-ohm meter to an operator interface control station. Eaton Predictive Diagnostics products such as the Insulgard™ partial discharge monitoring system have led the way in predicting future failures in large motors, generators and medium voltage switchgear well before the failures actually occurred. Be sure to read how the Forest Products Industry is working together with Eaton to drive toward this lower cost maintenance model.

Maintenance Method	Now	Target
Reactive	55%	16%
Preventative	31%	50%
Predictive	14%	33%