دانلود مقاله ISI انگلیسی شماره 22385
ترجمه فارسی عنوان مقاله

استفاده از کامپیوتر در سیستم مدیریت تعمیر و نگهداری بر اساس قابلیت اطمینان گیاه

عنوان انگلیسی
Computer-aided RCM-based plant maintenance management system
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
22385 2003 10 صفحه PDF
منبع

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

Journal : Robotics and Computer-Integrated Manufacturing, Volume 19, Issue 5, October 2003, Pages 449–458

ترجمه کلمات کلیدی
تعمیر و نگهداری بر اساس قابلیت اطمینان - مدیریت تعمیر و نگهداری - قابلیت اطمینان - تعمیر و نگهداری یکپارچه سیستم -
کلمات کلیدی انگلیسی
RCM, CMMS, Maintenance management, Reliability, Maintenance integrated system,
پیش نمایش مقاله
پیش نمایش مقاله  استفاده از کامپیوتر در سیستم مدیریت تعمیر و نگهداری بر اساس قابلیت اطمینان گیاه

چکیده انگلیسی

In most of the industries, classical reliability-centered maintenance (RCM) is employed to decide the maintenance strategies using reliability data without having adequate interaction with the design and operational systems. This means that the RCM process will be conducted with no or limited access to the design and operational data/knowledge. Commonly, the developed maintenance strategies are implemented and managed within the computerized maintenance management system (CMMS), which is usually separate from the RCM automated environment. This paper presents the detailed system design and mechanism of improved RCM process as integrated with CMMS. The proposed solution is integrated with design and operational systems and consolidates some successful maintainability approaches to formulate an effective solution for optimized plant maintenance. The major components of the enhanced RCM process are identified and a prototype system is implemented as integrated with the various modules of the adopted CMMS (MAXIMO™). A case study is used to show the effectiveness of the proposed RCM-based CMMS solution in optimizing plant maintenance over the traditional approaches.

مقدمه انگلیسی

The old maintenance practices that were commonly used, such as “Fix it when it breaks” or “Preventive maintenance”, could not achieve optimized maintenance with the current market challenges, while having high risk in operation [1]. In the early 1960s, the initial reliability-centered maintenance (RCM) development was done by the North American civil aviation industry. RCM process is intended to determine the most realistic and optimized maintenance requirements of any physical asset to continue its stated operating condition [2]. Many industries have adopted RCM technique to solve many confronted maintenance problems. Unfortunately, it did not work as expected for many reasons: (1) RCM is a time- and effort-consuming process and requires considerable amount of resources, especially for large number of assets for complex plants; (2) the available information is not adequate to decide the suitable maintenance strategy and to optimize its cost as maintenance and operational systems are isolated from design and engineering systems; (3) there are non-engineering factors involved in the maintenance problems i.e. management and human factors. To overcome some of the highlighted maintenance problems an integrated RCM-CMMS system is proposed so that it can dynamically change the maintenance strategies based on the operating condition of the equipment and other factors affecting the life (age) of the underlying assets. The background of the research idea can be approached from the following different angles:

نتیجه گیری انگلیسی

RCM-based CMMS is used to optimize maintenance for critical plants. The developed activity and function models are useful to understand such solution and to analyze other plants with minor modifications saving analysis time. The design modifications proposed to the adopted CMMS can be realized within MAXIMO, while RCMengine can be developed as a shell integrated with the different modules of MAXIMO. The integration with the plant design and operational systems is essential to share and utilize plant design model and plant operational information. Combined HAZOP, FMECA, and FTA are used to assess failure comprehensively (qualitatively and quantitatively). The offered solution can be further enhanced by utilizing Weibull and/or genetic algorithm modules to optimize the various parameters of the selected maintenance tasks.