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Journal ArticleDOI

Design and operational maintainability importance measures — A case study

TLDR
The aim of this paper is to define maintainability importance measures in order to find the criticality of each component or subsystem from the maintainability point of view.
Abstract
Performance of a system depends upon its components. Some components have major influences on system reliability and maintainability than others. Hence, several component importance measures have been well defined and widely used in the reliability area. These importance measures enable the weakest and most critical areas of a system to be identified, and which should be considered modified to improve the production plant performance. The aim of this paper is to define maintainability importance measures in order to find the criticality of each component or subsystem from the maintainability point of view. Such importance measures should be useful for resources allocation to improve production plant performance in both the design and operation phases.

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Citations
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Journal ArticleDOI

Criticality analysis of a production facility using cost importance measures

TL;DR: A cost importance measure is proposed which considers both the reliability and the maintainability information of a system and is studied in a simple oil and gas production system.
Journal ArticleDOI

Review and discussion of production assurance program

TL;DR: In this article, the authors reviewed, discussed and further developed the production assurance (PA) concept; and to define and describe a typical production assurance program (PAP) and its elements.
Journal ArticleDOI

Agile maintenance attribute coding and evaluation based decision making in sugar manufacturing plant

TL;DR: The proposed framework will act as decision support system for efficient planning of maintenance activities using exhaustive database of agile maintenance attributes and selecting effective maintenance strategy by integrating fuzzy methodology.
Book ChapterDOI

Assessing Maintenance Time, Cost and Uncertainty for Offshore Production Facilities in Arctic Environment

TL;DR: A method for maintenance cost and time assessments and their uncertainty, using the Monte Carlo simulation method is introduced and discusses, to be employed when designing for operation and maintenance in Arctic conditions of offshore production facilities.
Book ChapterDOI

Availability Importance Measure for Various Operation Condition

TL;DR: In this paper , the authors used the availability importance measure considering the operating environment for a mining fleet consisting of one shovel and six trucks, and analyzed the reliability and maintainability characteristic of machines considering all influence factors (covariates) using by Cox regression model.
References
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Book

An Introduction to Reliability and Maintainability Engineering

TL;DR: In this paper, the authors present a basic reliability model for failure distribution and a constant failure rate model for time-dependent failure models, as well as a design for maintainability.
Book

Reliability Engineering: Theory and Practice

Abstract: Basic Concepts, Quality and Reliability Assurance of Complex Equipment & Systems.- Reliability Analysis During the Design Phase.- Qualification Tests for Components and Assemblies.- Maintainability Analysis.- Design Guidelines for Reliability, Maintainability, and Software Quality.- Reliability and Availability of Repairable Systems.- Statistical Quality Control and Reliability Tests.- Quality & Reliability Assurance During the Production Phase.
ReportDOI

On the importance of different components in a multicomponent system

TL;DR: A quantitative definition of this notion of importance is proposed in the present paper for systems with coherent structures, assuming that only the structure of the system is known, or that also the reliabilities of all components are known.
Journal ArticleDOI

System reliability theory : models and statistical methods

Mark G. Vangel
- 01 Feb 1996 - 
TL;DR: In this paper, the authors present a Bayesian Reliability Data Sources and a Markov model for failure models. But they do not discuss the relationship between failure models and their components.
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