bibtype J - Journal Article
ARLID 0545784
utime 20220322093721.3
mtime 20210923235959.9
SCOPUS 85114143180
WOS 000702351700087
DOI 10.1016/j.ress.2021.108022
title (primary) (eng) An integrated methodological approach for optimising complex systems subjected to predictive maintenance
specification
page_count 16 s.
serial
ARLID cav_un_epca*0254891
ISSN 0951-8320
title Reliability Engineering & System Safety
volume_id 216
publisher
name Elsevier
keyword Complex systems
keyword DEMATEL
keyword ELECTRE TRI
keyword FMECA
keyword Maintenance management
keyword Predictive maintenance
keyword Risk management
author (primary)
ARLID cav_un_auth*0414171
name1 Ahmed
name2 U.
country IT
author
ARLID cav_un_auth*0398866
name1 Carpitella
name2 Silvia
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
country IT
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0399068
name1 Certa
name2 A.
country IT
source
url http://library.utia.cas.cz/separaty/2021/MTR/carpitella-0545784.pdf
source
url https://www.sciencedirect.com/science/article/pii/S0951832021005317
cas_special
abstract (eng) The present paper addresses the relevant topic of maintenance management, widely recognised as a fundamental issue involving complex engineering systems and leading companies towards the optimisation of their assets while pursuing cost efficiency. With this regard, our research aims to provide companies with a hybrid methodological approach based on Multi-Criteria Decision-Making (MCDM) capable to deal with the main failures potentially involving complex systems subjected to predictive maintenance. Such an approach is going to be integrated within the framework of traditional Failure Mode Effects and Criticality Analysis (FMECA), whose strengths and weaknesses are considered. In particular, the ELimination Et Choix Traduisant la REalité (ELECTRE) TRI is suggested to sort failure modes into risk priority classes while the Decision Making Trial and Evaluation Laboratory (DEMATEL) is proposed to highlight the most influencing failures within each risk class. The approach is applied to a real service system, whose critical components are monitored by sensors and subjected to predictive maintenance. Final results clearly demonstrate as highlighting the elements impacting the occurrence of other failures within specific risk classes is a significant driver towards the implementation of effective maintenance, maximising the whole level of performance of the analysed system over its lifecycle.
result_subspec SCOPUS
RIV AQ
FORD0 30000
FORD1 30300
FORD2 30305
reportyear 2022
num_of_auth 3
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0322773
mrcbC61 1
confidential U
article_num 108022
mrcbC86 1 Article Engineering Industrial|Operations Research Management Science
mrcbC91 C
mrcbT16-e ENGINEERINGINDUSTRIAL|OPERATIONSRESEARCHMANAGEMENTSCIENCE
mrcbT16-j 1.04
mrcbT16-s 1.824
mrcbT16-D Q3
mrcbT16-E Q1
arlyear 2021
mrcbU14 85114143180 SCOPUS
mrcbU24 PUBMED
mrcbU34 000702351700087 WOS
mrcbU63 cav_un_epca*0254891 Reliability Engineering & System Safety 0951-8320 1879-0836 Roč. 216 č. 1 2021 Elsevier