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Title:Weibull decision support systems in maintenance
Authors:ID Aboura, Khalid (Author)
ID Agbinya, Johnson (Author)
ID Eskandarian, Ali (Author)
Files:.pdf Organizacija_2014_Aboura,_Agbinya,_Eskandarian_Weibull_Decision_Support_Systems_in_Maintenance.pdf (527,86 KB)
MD5: BAF0788C95FBA9ED7D2FFDE7CF87D27F
PID: 20.500.12556/dkum/d2b111e2-f3ae-4777-b292-722e4b007255
 
URL http://www.degruyter.com/view/j/orga.2014.47.issue-2/orga-2014-0008/orga-2014-0008.xml
 
Language:English
Work type:Scientific work (r2)
Typology:1.01 - Original Scientific Article
Organization:FOV - Faculty of Organizational Sciences in Kranj
Abstract:Background: The Weibull distribution is one of the most important lifetime distributions in applied statistics. Weibull analysis is the leading method in the world for fitting and analyzing lifetime data. We discuss one of the earliest decision support system for the assessment of a distribution for the parameters of the Weibull reliability model using expert information. We then present a different approach to assess the parameters distribution. Objectives: The studies mentioned in this paper aimed to construct a distribution of the parameters of the Weibull reliability model and apply it in the domain of Maintenance Optimization. Method: The parameters of the Weibull reliability model are considered random variables and a distribution for the parameters is assessed using informed judgment in the form of reliability estimates from vendor information, engineering knowledge or experience in the field. Results: The results are the development of modern maintenance optimization models that can be embodied in decision support systems. Conclusion: While the information management part is important in the building of maintenance optimization decision systems, the accuracy of the mathematical and statistical algorithms determines the level of success of the maintenance solution.
Keywords:Weibull distribution, reliability, inference, maintenance, expert opinion
Year of publishing:2014
Publication status in journal:Published
Article version:Publisher's version of article
Number of pages:str. 81-89
Numbering:Letn. 47, št. 2
PID:20.500.12556/DKUM-69449 New window
ISSN:1318-5454
UDC:005.591.1:311.15
ISSN on article:1318-5454
COBISS.SI-ID:279073280 New window
DOI:10.2478/orga-2014-0008 New window
NUK URN:URN:SI:UM:DK:XIEESHAB
Publication date in DKUM:23.01.2018
Views:916
Downloads:318
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Organizacija. revija za management, informatiko in kadre
Shortened title:Organizacija
Publisher:Moderna organizacija
ISSN:1318-5454
COBISS.SI-ID:610909 New window

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:23.01.2018

Secondary language

Language:Slovenian
Title:Sistem za podporo odločanju vzdrževanja na podlagi Weibullove porazdelitve
Abstract:Ozadje: Weibullova porazdelitev je ena od najbolj pomembnih na področju porazdelitev življenjske dobe v uporabni statistiki. Ona je vodilna metoda za oceno in analizo podatkov na področju življenjske dobe. V prispevku razpravljamo o enem od prvih sistemov za podporo odločanju za oceno porazdelitve parametrov zanesljivosti Weibull-ovega modela na podlagi razpoložljive informacije. Nato smo predstavili drugačen pristop za oceno porazdelitve parametrov . Cilji: Cilj študije je zgraditi model porazdelitve parametrov zanesljivosti Weibullove porazdelitve in ga uporabiti na področju optimizacije vzdrževanja. Metoda: Parametri modela Weibullove zanesljivosti obravnavamo kot naključne spremenljivke katerih distribucija je ocenjena z strani ekspertov v obliki zanesljivosti s pomočjo informacij prodajalca z inženirskim znanjem in izkušnjami na tem področju. Rezultat: Rezultati so razvoj sodobnih optimizacijskih modelov za vzdrževanje kot sistem za podporo odločanju vzdrževanja. Zaključek: Medtem ko je del za upravljanje informacij pomemben pri gradnji sistemov za podporo odločanja optimizacije vzdrževanja, zanesljivost matematičnih in statističnih algoritmov določa stopnjo uspešnosti rešitev za vzdrževanje.
Keywords:podjetja, vzdrževanje, odločanje, optimiranje, statistične metode, zanesljivost


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This document is a part of these collections:
  1. Organizacija

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