Bayesian Analysis of Expert Elicitation Responses for Life Cycle Management Replacement Probability Estimates

2017 ◽  
Author(s):  
Joseph Cluever ◽  
Thomas Esselman ◽  
Sam Harvey
Keyword(s):  
Life Cycle ◽  
Bayesian Analysis ◽  
Computer Code ◽  
Life Cycle Management ◽  
Expert Elicitation ◽  
Maintenance Cost ◽  
Probability Estimates ◽  
Standard Tool ◽  
Expert’S Opinion ◽  
Effective Decision Making

In 2014, the Integrated Life Cycle Management (ILCM) computer code was developed through collaboration between the Electric Power Research Institute (EPRI) and Électricité de France (EDF) to provide a standard methodology to support effective decision making for the long-term management of selected station assets. In order for the ILCM program to become a standard tool in the industry, additional work was needed in the development of a Likelihood of Replacement (LoR) calculator. The LoR calculator estimates the likelihood that a component will have to be replaced due to failure or reasons other than failure, such as high maintenance cost, inability to maintain, obsolescence, and other similar reasons. Expert elicitation was chosen as the method of gathering data and opinions on component replacement probabilities. The majority of expert elicitation techniques consist of experts giving opinions on the probability of replacement at various points in time, from which a reliability curve can be calculated. Furthermore, any failure or replacement data is subjectively incorporated in to the expert’s opinion. The present work uses Bayesian analysis to provide an objective method for statistically combining expert opinion with failure and replacement data. This paper also describes the process of extracting a Weibull LoR curve from expert’s opinions and reported failures and replacements. The expert’s work history and answer confidence is used to assign uncertainty in their answers and calculate 5th, 50th, and 95th percentile credibility Weibull curves for the probability of replacement.

Estimation of Weibull Life Distributions From Expert Categorical Estimates of Failure Probabilities

2018 ◽  
Author(s):  
Joseph Cluever ◽  
Thomas Esselman ◽  
Sam Harvey
Keyword(s):  
Parameter Uncertainty ◽  
Computer Code ◽  
Life Cycle Management ◽  
Expert Elicitation ◽  
Likelihood Functions ◽  
Probability Estimates ◽  
Effective Decision ◽  
Life Distributions ◽  
Effective Decision Making

The Electric Power Research Institute (EPRI) with Électricité de France (EDF) developed the Integrated Life Cycle Management (ILCM) computer code to provide a standard methodology to support effective decision making for the long-term management of selected nuclear station components. In 2016, a Likelihood of Replacement (LoR) expert elicitation was developed to provide reliability curves for determination of replacement options for components that were not initially included in ILCM. The LoR methodology required expert’s to estimate future replacement probabilities which were then combined with historical failures using Bayesian analysis. Although this methodology was effective, parts of the industry were accustomed to providing a High/Medium/Low (HML) probability categorization for selected periods of operation. This paper presents an approach for calculating Weibull replacement probability curves from HML categorical replacement probability estimates. Additional questions beyond the initial HML categorization were developed. These focused on the timing of category transitions to refine parameter likelihood functions, reduce parameter uncertainty, and offset the significant Weibull parameter uncertainty introduced by using categorical estimates.

Effectiveness Of Life Cycle Management Of Projects Using Information Modeling

2019 ◽  
pp. 24-29 ◽  
Keyword(s):  
Life Cycle ◽  
Construction Projects ◽  
Life Cycle Management ◽  
Information Modeling ◽  
Engineering Systems ◽  
Basic Principles ◽  
Complex Engineering ◽  
Domestic Practices ◽  
Capital Construction ◽  
Complex Engineering Systems

Improving the efficiency of life cycle management of capital construction projects using information modeling technologies is one of the important tasks of the construction industry. The paper presents an analysis of accumulated domestic practices, including the legal and regulatory framework, assessing the effectiveness of managing the implementation of investment construction projects and of complex and serial capital construction projects, as well as the life cycle management of especially dangerous technically complex and unique capital construction projects using information modeling technologies, especially capital construction projects, as well as their supporting and using systems, primarily in the nuclear and transport sectors. A review of modern approaches to assessing the effectiveness of life cycle management systems of complex engineering systems in relation to capital construction projects is carried out. The presented material will make it possible to formulate the basic principles and prospects of applying approaches to assessing the effectiveness of the life cycle management system of a capital construction project using information modeling technologies.

Life Cycle of Construction Objects at Information Simulation of Buildings and Structures

2019 ◽  
pp. 65-72 ◽  
Keyword(s):  
Life Cycle ◽  
Construction Projects ◽  
Life Cycle Management ◽  
Information Modeling ◽  
Sources Of Information ◽  
Logical Scheme ◽  
Modeling Technology ◽  
Information Models ◽  
Building Information ◽  
The Russian Federation

The variants of the division of the life cycle of a construction object at the stages adopted in the territory of the Russian Federation, as well as in other countries are considered. Particular attention is paid to the exemplary work plan – "RIBA plan of work", used in England. A feature of this document is its applicability in the information modeling of construction projects (Building information Modeling – BIM). The article presents a structural and logical scheme of the life cycle of a building object and a list of works that are performed using information modeling technology at various stages of the life cycle of the building. The place of information models in the process of determining the service life of the building is shown. On the basis of the considered sources of information, promising directions for the development of the life cycle management system of the construction object (Life Cycle Management) and the development of the regulatory framework in order to improve the use of information modeling in construction are given.

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