Plant Services - August 2007 - (Page 44) RELIABILITY Motors operating in an OEM’s product, the realities of the global market provide common ground for the way users approach motor issues. Industries, manufacturers and end users are under pressure to reduce the cost of production, products and warranty claims just to stay competitive. In the quest to reduce costs, every dollar counts and the cost of the drive motor is a primary item that comes up frequently. For large facilities, OEMs or anyone who buys motors by the truckload, a dollar of unit cost saved is a big deal. When motor cost is on the radar screen, it’s important to evaluate the reliability of a manufacturer’s offerings against the motor that’s been giving you a headache. The number of candidates depends on the confidence level you require and how much you want to spend on the evaluation. If your motors have been reliable in the past, you’re faced with tough questions: • How do we move to a new, unfamiliar motor? • How can we make sure it will work well here? • How will this change affect our life-cycle cost? These are but a few questions that arise, and getting answers isn’t easy because the answers are inextricably linked to motor reliability. Testing, testing Figure 2. Reliability testing rig is used for smaller motors. nential distribution, the mean time between failure and the reliability function (R(t)) are expressed as: MTBF = Total operating time/Number of failures Define motor reliability Reliability is the probability that a system will perform satisfactorily for at least a given time period when used under stated conditions. This probability, expressed as a function of time, is called the reliability function, R(t). For years, reliability engineers have used mean-time-to-failure (MTTF) to measure reliability for non-repairable equipment, and mean-time-between-failures (MTBF) for repairable equipment. Assuming a constant failure rate ( ) and an expo- Trade quantity for time 80 70 Number of samples 60 50 40 30 20 10 0 0 2,000 4,000 6,000 Hours of testing required 8,000 Hours = 2,500 Shape parameter = 1.5 Rel = 95% C.L. = 80% Properly applied motors usually exhibit high reliability and also are generally repairable. However, in most cases, it makes more sense to replace small motors than to repair them. The events that are considered as total or partial failure will vary by equipment type and by plant. While total failure is easily understood, partial failure is difficult to generalize and the user must define it depending on the level of trouble-free operation required. From the definition of MTBF, it’s clear that quantifying reliability requires accurate and dependable data. Plant personnel can collect dependable historical failure data during operation and use it to evaluate reliability, but this is much more involved than it seems because plant personnel must take note of the reasons for failure, which could be time consuming or impossible. Also, the operating environment must be recorded because different motors in different environments are exposed to different conditions. Another way to get failure data is through model predictions, which analyze equipment and system components to determine the failure rate of the entire assembly by using complex mathematical formulations. The empirical method for getting failure data is through testing. This approach is more suitable for small motors. Reliability tests Figure 1. Sample quantity versus test duration to demonstrate 95% reliability at 80% confidence with no failures allowed. You might need a number expressing motor reliability for some critical process. Obtain this reliability number by a carefully designed testing of a number of identical units. There are two main ways this can be achieved. The first involves measuring the time to failure for a August 2007 44 www.PLANTSERVICES.com http://www.PLANTSERVICES.com
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