Development of a risk-based maintenance decision making approach for automotive production line
Document identifier: oai:DiVA.org:ltu-77162
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10.1007/s13198-019-00927-1Keyword: Engineering and Technology,
Civil Engineering,
Other Civil Engineering,
Teknik och teknologier,
Samhällsbyggnadsteknik,
Annan samhällsbyggnadsteknik,
Automotive industry,
Fuzzy set theory,
Maintenance decision making,
RPN value,
Sensitivity analysis,
Drift och underhållsteknik,
Operation and MaintenancePublication year: 2020Abstract: Automotive industries require effective and reliable maintenance strategies to ensure high levels of availability and safety. Risk-based maintenance approach is a useful tool for maintenance decision making with the aim of reducing the overall risk in operating activities. In this paper, a Failure Mode and Effect Analysis (FMEA) model as one of the risk assessment techniques is developed with subjective information derived from domain experts. To overcome the drawbacks of traditional FMEA for risk priority number (RPN) estimation, a linguistic fuzzy set theory, through effective decision attributes in complex automotive equipment is conducted. The main attributes of this approach include the effect of experts’ traits, scales variation, using various membership functions and defuzzification algorithms on reliable Fuzzy-RPN (FRPN) estimation. The result of the proposed model revealed that altering membership functions and defuzzification algorithms had no significant effect on the FRPN estimation, but their values are highly affected by the number of scales. The sensitivity analysis showed that experts’ traits have no sensible impact on experts’ opinion for FRPN estimation, while the detectability index has more impact on FRPN variation. The result of risk classification number showed that the maintenance decision making could be included for the failure modes with the highest RPN values as a priority, which it would be useful to achieve the high level of availability and safety.
Authors
Hamzeh Soltanali
Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Other publications
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Abbas Rohani
Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
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>>
Mohammad Hossein Abbaspour-Fard
Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
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>>
Aditya Parida
Luleå tekniska universitet; Drift, underhåll och akustik
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José Torres Farinha
Centre for Mechanical Engineering, Materials and Processes (CEMMPRE), ISEC - Coimbra Institute of Engineering, Coimbra, Portugal
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>>
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header:
identifier: oai:DiVA.org:ltu-77162
datestamp: 2021-04-19T12:41:07Z
setSpec: SwePub-ltu
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recordContentSource: ltu
recordCreationDate: 2019-12-12
identifier:
http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-77162
10.1007/s13198-019-00927-1
2-s2.0-85076739491
titleInfo:
@attributes:
lang: eng
title: Development of a risk-based maintenance decision making approach for automotive production line
abstract: Automotive industries require effective and reliable maintenance strategies to ensure high levels of availability and safety. Risk-based maintenance approach is a useful tool for maintenance decision making with the aim of reducing the overall risk in operating activities. In this paper a Failure Mode and Effect Analysis (FMEA) model as one of the risk assessment techniques is developed with subjective information derived from domain experts. To overcome the drawbacks of traditional FMEA for risk priority number (RPN) estimation a linguistic fuzzy set theory through effective decision attributes in complex automotive equipment is conducted. The main attributes of this approach include the effect of experts’ traits scales variation using various membership functions and defuzzification algorithms on reliable Fuzzy-RPN (FRPN) estimation. The result of the proposed model revealed that altering membership functions and defuzzification algorithms had no significant effect on the FRPN estimation but their values are highly affected by the number of scales. The sensitivity analysis showed that experts’ traits have no sensible impact on experts’ opinion for FRPN estimation while the detectability index has more impact on FRPN variation. The result of risk classification number showed that the maintenance decision making could be included for the failure modes with the highest RPN values as a priority which it would be useful to achieve the high level of availability and safety.
subject:
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Civil Engineering
Other Civil Engineering
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Samhällsbyggnadsteknik
Annan samhällsbyggnadsteknik
@attributes:
lang: eng
topic: Automotive industry
@attributes:
lang: eng
topic: Fuzzy set theory
@attributes:
lang: eng
topic: Maintenance decision making
@attributes:
lang: eng
topic: RPN value
@attributes:
lang: eng
topic: Sensitivity analysis
@attributes:
lang: swe
authority: ltu
topic: Drift och underhållsteknik
genre: Research subject
@attributes:
lang: eng
authority: ltu
topic: Operation and Maintenance
genre: Research subject
language:
languageTerm: eng
genre:
publication/journal-article
ref
note:
Published
5
Validerad;2020;Nivå 2;2020-03-10 (johcin)
name:
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type: personal
namePart:
Soltanali
Hamzeh
role:
roleTerm: aut
affiliation: Department of Biosystems Engineering Ferdowsi University of Mashhad Mashhad Iran
@attributes:
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namePart:
Rohani
Abbas
role:
roleTerm: aut
affiliation: Department of Biosystems Engineering Ferdowsi University of Mashhad Mashhad Iran
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namePart:
Abbaspour-Fard
Mohammad Hossein
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roleTerm: aut
affiliation: Department of Biosystems Engineering Ferdowsi University of Mashhad Mashhad Iran
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authority: ltu
namePart:
Parida
Aditya
role:
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affiliation:
Luleå tekniska universitet
Drift underhåll och akustik
nameIdentifier:
parkum
0000-0002-7474-2723
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Farinha
José Torres
role:
roleTerm: aut
affiliation: Centre for Mechanical Engineering Materials and Processes (CEMMPRE) ISEC - Coimbra Institute of Engineering Coimbra Portugal
originInfo:
dateIssued: 2020
publisher: Springer
relatedItem:
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titleInfo:
title: International Journal of Systems Assurance Engineering and Management
identifier:
0975-6809
0976-4348
part:
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@attributes:
type: volume
number: 11
@attributes:
type: issue
number: 1
extent:
start: 236
end: 251
physicalDescription:
form: print
typeOfResource: text