11,396 research outputs found
Estimation of component redundancy in optimal age maintenance
The classical Optimal Age-Replacement defines the maintenance strategy based on the equipment failure consequences. For severe consequences an early equipment replacement is recommended. For minor consequences the repair after failure is proposed. One way of reducing the failure consequences is the use of redundancies, especially if the equipment failure rate is decreasing over time, since in this case the preventive replacement does not reduce the risk of failure.
The estimation of an active component redundancy degree is very important in order to minimize the life-cycle cost. If it is possible to make these estimations in the early phase of system design, the implementation is easier and the amortization faster.
This work proposes an adaptation of the Optimal Age-Replacement method in order to simultaneously optimize the equipment redundancy allocation and the maintenance plan. The main goal is to provide a simple methodology, requiring the fewer data possible.
A set of examples are presented illustrating that this methodology covers a wide variety of operating conditions. The optimization of the number of repairs between each replacement, in the cases of imperfect repairs, is another feature of this methodology
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Investigation of Ageing Effects Using the Probabilistic Safety Assessments - Proceedings of the European Workshop on Probabilistic Safety Assessment
JRC – IE Petten organized with the support of the Kernkraftwerk Gösgen-Däniken, Switzerland, an EC Workshop on Investigation of Ageing Effects using the Probabilistic Safety Assessments.
The goal of the workshop was to present and discuss the developed methods and approaches and the results obtained for application of reliability and PSA techniques on evaluation and management of NPP ageing.
For the units which have approached the end of initial design lifetime and especially for those which are planning to extend the lifetime, it has to be demonstrated that the plant safety level will remain adequate until the end of operation, and to do that, is necessary to evaluate the effects of ageing phenomena on the plant performance and safety.
The workshop contained a general session, dedicated to activities of different organizations in PSA field, and a technical session, focused on the results obtained in application of reliability and PSA techniques on evaluation and management of NPP ageing.
Based on the presentations and participants experience, discussions about topics considered interested to be developed further were organized. The arising conclusions are presented.JRC.F.5-Nuclear Reactor Safety Assessmen
Cost Benefit Evaluation of Maintenance Options for Aging Equipment Using Monetised Risk Values: A practical application
With constant pressure to reduce maintenance costs as well as short-term budget constraints in a changing market environment, asset managers are compelled to continue operating aging assets while deferring maintenance and investment. The scope of the paper is to get an overview of the methods used to evaluate risks and opportunities for deferred maintenance interventions on aging equipment, and underline the importance to include monetised risk considerations and timeline considerations, to evaluate different scenarios connected with the possible options. Monetised risk values offer the opportunity to support risk-based decision-making using the data collected from the field. The paper presents examples of two different methods and their practical applicability in two case studies in the energy sector for a company managing power stations. The use of the existing and the new proposed solutions are discussed on the basis of their applicability to the concrete examples
Cost benefit evaluation of maintenance options for aging equipment using monetised risk values: A practical application
With constant pressure to reduce maintenance costs as well as short-term budget constraints in a changing market environment, asset managers are compelled to continue operating aging assets while deferring maintenance and investment. The scope of the paper is to get an overview of the methods used to evaluate risks and opportunities for deferred maintenance interventions on aging equipment, and underline the importance to include monetised risk considerations and timeline considerations, to evaluate different scenarios connected with the possible options. Monetised risk values offer the opportunity to support risk-based decision-making using the data collected from the field. The paper presents examples of two different methods and their practical applicability in two case studies in the energy sector for a company managing power stations. The use of the existing and the new proposed solutions are discussed on the basis of their applicability to the concrete examples
Maintenance Strategy Choice Supported by the Failure Rate Function: Application in a Serial Manufacturing Line
The purpose of this article is to choose a maintenance procedure for the critical equipment of a forging production line with five machines. The research method is quantitative modelling and simulation. The main research technique includes retrieving time between failure and time to repair data and find the most likely distribution that has produced the data. The most likely failure rate function helps to define the maintenance strategy. The study includes two kinds of maintenance policies, reactive and anticipatory. Reactive policies include emergency and corrective procedures. Anticipatory policies include predictive and preventive ones combined with a total productive maintenance management approach. The most suitable combination for the first three machines is emergency and corrective choice. For the other machines, a combination of total productive maintenance and a predictive approach is optimal. The study encompasses the case of a serial production manufacturing line and maximum likelihood estimation. The failure rate function defines a combination of strategies for each machine. In addition, the study calculates the individual and systemic mean time to failure, mean time to repair, availability, and the most likely number of failures per production order, which follows a Poisson process. The main contribution of the article is a structured method to help define maintenance choices for critical equipment based on empirical data
RELIABILITY CENTERED MAINTENANCE (RCM) FOR ASSET MANAGEMENT IN ELECTRIC POWER DISTRIBUTION SYSTEM
The purpose of Maintenance is to extend equipment life time or at least the mean
time to the next failure.
Asset Maintenance, which is part of asset management, incurs expenditure but
could result in very costly consequences if not performed or performed too little.
It may not even be economical to perform it too frequently.
The decision therefore, to eliminate or minimize the risk of equipment failure
must not be based on trial and error as it was done in the past.
In this thesis, an enhanced Reliability-Centered Maintenance (RCM)
methodology that is based on a quantitative relationship between preventive
maintenance (PM) performed at system component level and the overall system
reliability was applied to identify the distribution components that are critical to
system reliability.
Maintenance model relating probability of failure to maintenance activity was
developed for maintainable distribution components. The Markov maintenance
Model developed was then used to predict the remaining life of transformer
insulation for a selected distribution system. This Model incorporates various
levels of insulation deterioration and minor maintenance state. If current state of
insulation ageing is assumed from diagnostic testing and inspection, the Model is
capable of computing the average time before insulation failure occurs.
The results obtained from both Model simulation and the computer program of
the mathematical formulation of the expected remaining life verified the
mathematical analysis of the developed model in this thesis.
The conclusion from this study shows that it is beneficial to base asset
management decisions on a model that is verified with processed, analysed and
tested outage data such as the model developed in this thesis
Prognostics and Health Management of Industrial Equipment
ISBN13: 9781466620957Prognostics and health management (PHM) is a field of research and application which aims at making use of past, present and future information on the environmental, operational and usage conditions of an equipment in order to detect its degradation, diagnose its faults, predict and proactively manage its failures. The present paper reviews the state of knowledge on the methods for PHM, placing these in context with the different information and data which may be available for performing the task and identifying the current challenges and open issues which must be addressed for achieving reliable deployment in practice. The focus is predominantly on the prognostic part of PHM, which addresses the prediction of equipment failure occurrence and associated residual useful life (RUL)
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