دانلود مقاله ISI انگلیسی شماره 47131
ترجمه فارسی عنوان مقاله

تعمیر و نگهداری پیشگویانه چند سطحی برای سیستمهای چند جزئی

عنوان انگلیسی
Multi-level predictive maintenance for multi-component systems
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
47131 2015 12 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Reliability Engineering & System Safety, Volume 144, December 2015, Pages 83–94

ترجمه کلمات کلیدی
سیستمهای چند جزئی - شرط بر اساس تعمیر و نگهداری - فرصت طلب - وابستگی اقتصادی - پیش آگهی - اهمیت اندازه گیری - تعمیر و نگهداری مبتنی بر شرایط - فرصت طلب و اصلاح و پیشگیری - - حداقل برش در ماه سپتامبر - وابستگی اقتصادی مثبت و منفی - - بلوک دیاگرام قابلیت اطمینان - عمر مفید باقی مانده
کلمات کلیدی انگلیسی
Multi-component system; Condition-based maintenance; Opportunistic; Economic dependencies; Prognostic; Importance measureCBM, condition-based maintenance; CM & OM & PM, corrective and opportunistic and preventive maintenance; MCS, minimal cut set; NED & PED, negative and positive economic dependence; RBD, reliability block diagram; RUL, remaining useful life
پیش نمایش مقاله
پیش نمایش مقاله  تعمیر و نگهداری پیشگویانه چند سطحی برای سیستمهای چند جزئی

چکیده انگلیسی

In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenance actions are needed regarding the predictive reliability of the system. At component level the decision rules aim at identifying optimally a group of several components to be preventively maintained when preventive maintenance is trigged due to the system level decision. Selecting optimal components is based on a cost-based group improvement factor taking into account the predictive reliability of the components, the economic dependencies as well as the location of the components in the system. Moreover, a cost model is developed to find the optimal maintenance decision variables. A 14-component system is finally introduced to illustrate the use and the performance of the proposed predictive maintenance policy. Different sensitivity analysis are also investigated and discussed. Indeed, the proposed policy provides more flexibility in maintenance decision-making for complex structure systems, hence leading to significant profits in terms of maintenance cost when compared with existing policies.