تعمیر و نگهداری بر اساس قابلیت اطمینان + C تصمیم گیری آگاهانه و کاربرد آن در بهینه سازی چند هدفه مشخصات فنی تعمیر و نگهداری با استفاده از الگوریتم ژنتیک
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|22388||2005||11 صفحه PDF||سفارش دهید||6417 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Reliability Engineering & System Safety, Volume 87, Issue 1, January 2005, Pages 65–75
The role of technical specifications and maintenance (TSM) activities at nuclear power plants (NPP) aims to increase reliability, availability and maintainability (RAM) of Safety-Related Equipment, which, in turn, must yield to an improved level of plant safety. However, more resources (e.g. costs, task force, etc.) have to be assigned in above areas to achieve better scores in reliability, availability, maintainability and safety (RAMS). Current situation at NPP shows different programs implemented at the plant that aim to the improvement of particular TSM-related parameters where the decision-making process is based on the assessment of the impact of the change proposed on a subgroup of RAMS+C attributes. This paper briefly reviews the role of TSM and two main groups of improvement programs at NPP, which suggest the convenience of considering the approach proposed in this paper for the Integrated Multi-Criteria Decision-Making on changes to TSM-related parameters based on RAMS+C criteria as a whole, as it can be seem as a decision-making process more consistent with the role and synergic effects of TSM and the objectives and goals of current improvement programs at NPP. The case of application to the Emergency Diesel Generator system demonstrates the viability and significance of the proposed approach for the Multi-objective Optimization of TSM-related parameters using a Genetic Algorithm.
The study of changes to TSM at NPP normally aims at finding the best solution feasible for a particular requirement or activity (Maintenance, SR, LCO, etc.), taking into account relevant criteria concerning the decision-making; that is for example, searching the appropriate set of particular parameters related to TSM of SRE to result in minimal risk, cost, etc. In this way, one can find in the literature several analyses of changes to particular parameters related to TSM that have been performed at NPP taking as reference the information provided by the analysis of the risk impact of the changes proposed, which fall into the well know group of risk-informed applications to support decision-making. Among the application areas one can find risk-informed improvement or optimization of STI and AOT both within the Technical Specification. In addition, there are many works in the literature devoted to the analysis of changes or even optimization of maintenance-related parameters at NPP where the RAM of systems and components that overcome maintenance activities are adopted as decision criteria ,  and . Furthermore, recent works often take into consideration additional acceptance criteria for the decision-making procedure; such as economical costs, human resources, etc., that yield to an IMCDM on changes to TSM-related parameters in many applications , ,  and . This paper briefly reviews the role of TSM to achieve appropriate levels of RAMS of NPP. Then, the ongoing programmes or those being currently considered for implementation at NPPs that aim at improving both maintenance practices and TS that justify the need of such IMCDM are introduced. Starting from the analysis of the current situation, a new IMCDM approach based on RAMS+C criteria to assess changes to TSM-related parameters is proposed. This approach extends the current concept of Risk-informed to a RAMS+C-informed decision-making integrating many of the TSM requirements, activities and multiple acceptance criteria at NPP. This methodology can consider other traditional criteria such as human resources, radiological doses, etc. The application performed on a safety system normally in standby of a NPP reveals the significance of the proposed approach and assesses the viability of the proposed methodology to solve this kind of engineering problems formulated as a multi-objective optimization problem.