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6 benefits of using predictive maintenance

Posted by Bala Deshpande on Tue, Feb 04, 2014 @ 07:38 AM

This article was contributed by Vaibhav Waghmare.

Today, advantages of predictive maintenance are accepted in many industries and it hasvibration analyzers for fault detection failure prediction 2 resized 600 become an essential tool, because of its efficiency in fault detection during early stages and thus reducing unscheduled down time. It increases productivity, improves quality and provides the feeling of safety and reliability to staff. In process industries, such as cement, sugar, chemical, power generation and others even a small downtime costs much and is an over-riding reason to accept and implement predictive maintenance in plants.

In a previous article Predictive maintenance: key challenges to increase adoption we identified key challenges to adopt PM. In another article we saw how predictive maintenance can improve equipment maintenance. This article provides an introduction to the cost-benefit analysis when predictive maintenance is applied to vibrating machinery.

Vibration analysis is one of the most commonly used predictive maintenance technologies in industry. Through the utilization of instrumentation, equipment condition is monitored and internal component faults are identified, measured, and quantified. Through this process, critical failure of mechanical equipment can be avoided while extending the life cycle of monitored equipment. Machinery problems occur at specific frequencies, vibration analysis can pinpoint problems without guesswork. Vibration analysis gives you the information you need for accepting new equipment, identifying problems for repair and after overhaul to assure machinery reliability. There are multiple cost benefits after using Vibration analysis. In this analysis process vibration sensors are places on equipment and the data is collected, processed and alerts are generated based on the vibration pattern. As soon as some alert or warning is generated based on specific vibration pattern, a maintenance is scheduled during non-working hours and the machine is repaired before it fails. Following are different cost benefits of using predictive maintenance.

COST BENEFITS OF VIBRATION ANALYSIS

  1. Reduces equipment costs - instead of replacement of the entire piece of equipment due to critical failure, a repair is made prior to failure and cost is minimized to the price of the component and the labor needed for the repair.
  2. Reduces labor costs - When repairs are scheduled, the amount of time needed for repair is reduced because of a smaller number of component replacements instead of entire equipment replacement. Also, the frequency of repair for critical failure of equipment will be reduced and the amount of “critical callouts” will be greatly reduced.
  3. Reduces lost production time - Component only replacement is scheduled with production to take place during scheduled downtime. Unscheduled downtime may cost thousands of dollars per hour. A proactive maintenance department can head off critical failure downtime by scheduling repair during non-productive times.
  4. Increases safety - Predictive maintenance would allow potential problems to be fixed before failure occurs, which would create safer driving conditions for employees and customers.
  5. Increases revenue - With less maintenance on good components and quicker repair of faulty components, repairs can be more effectively handled, thereby reducing repair time.
  6. Increases efficiency of employee time - By identifying the precise repair task needed to correct deficiencies, as well as the parts, tools and support needed to correct the problem can dramatically increase effective "wrench time."

This simple custom dashboard describes how the cost benefits of predictive maintenance or condition based maintenance can be visualized.

predictive maintenance example bearing repair costs resized 600

Join us at the first ever Predictive Analytics World-Manufacturing conference to learn about predictive maintenance in practice.

predictive analytics world manufacturing 2014

Topics: predictive analytics, manufacturing analytics, machine data analytics

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