آشکارسازی تجهیزات بالا رفتن سن و تعیین بهره وری از اندازه گیری اصلاحی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|22387||2004||8 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Reliability Engineering & System Safety, Volume 84, Issue 1, April 2004, Pages 57–64
When too many failures occur on a given piece of equipment, the dependability engineer needs to decide whether these failures are attributable to poor initial design or if they are due to a phenomenon of aging. If aging is confirmed, the problem is then to determine the moment at which the process began and what corrective measure (generally, a modification in the design or in the preventive maintenance program) is the best suited to delay the occurrence of the failure. This measure will thus make it possible to extend the lifetime of the equipment.The method is based on the simple hypothesis of a model of step aging and on Bayesian techniques. The principal benefit of this method is the determination of the time at which aging begins (and the related uncertainties), the evolution in the failure rate of the component in its initial state and once modified, and the probability of success of the corrective measure. The IBTV software was developed to implement this methodology
One practical problem frequently encountered by dependability engineers in cases where an excessive number of equipment failures have been observed is determining whether the failures are in fact due to a phenomenon of early aging of the equipment. If aging is confirmed, the problem is then to determine the moment in time when the process began and what corrective measures (preventive maintenance operation or a modification in the design or actual replacement) will best help to delay the occurrence of a failure. Finally, once new feedback has been collected, one must determine the efficiency of the corrective measure chosen. The first part of this paper presents the overall context of this study; the Bayesian methodology used is then described, as are the objectives of specific software developed for this purpose (IBTV: ‘Inférence Bayésienne pour le Traitement du Vieillissement’—Bayesian inference for treatment of aging); the last part of the paper presents some concrete applications and comparisons.
نتیجه گیری انگلیسی
Component aging may be represented by the accumulation of failures around the term of a mean lifetime. This is shown by a step model which is very simple to use and to interpret. Simplicity and relative easy physical interpretation are the two major arguments of use of the method. The IBTV software has been developed, tested on simulated and real applications and compared in terms of results with other methods. The greater the number of failures observed, the better are the results. Once again, therefore, it is to be strongly recommended that feedback data be collected and validated before being used. Finally, this model is particularly useful in practice when one wishes to determine what changes are needed in maintenance programs, in the Reliability Centered Maintenance framework, or to define scenarios for maintenance, design changes or replacement in the framework of management of the life cycle of any component.