| bibtype |
J -
Journal Article
|
| ARLID |
0545774 |
| utime |
20220927164646.9 |
| mtime |
20210923235959.9 |
| SCOPUS |
85089512877 |
| WOS |
000564445500001 |
| DOI |
10.1108/JQME-11-2019-0107 |
| title
(primary) (eng) |
A decision support system to assure high performance maintenance service |
| specification |
| page_count |
20 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0545773 |
| ISSN |
1355-2511 |
| title
|
Journal of Quality in Maintenance Engineering |
| volume_id |
27 |
| volume |
4 (2021) |
| page_num |
651-670 |
| publisher |
|
|
| keyword |
Decision support system |
| keyword |
Predictive maintenance |
| keyword |
Key performance indicator |
| keyword |
Maintenance planning |
| author
(primary) |
| ARLID |
cav_un_auth*0414158 |
| name1 |
Aiello |
| name2 |
G. |
| country |
IT |
|
| author
|
| ARLID |
cav_un_auth*0414159 |
| name1 |
Benítez |
| name2 |
J. |
| country |
ES |
|
| 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*0414160 |
| name1 |
Certa |
| name2 |
A. |
| country |
IT |
|
| author
|
| ARLID |
cav_un_auth*0414161 |
| name1 |
Enea |
| name2 |
M. |
| country |
IT |
|
| author
|
| ARLID |
cav_un_auth*0256480 |
| name1 |
Izquierdo |
| name2 |
J. |
| country |
ES |
|
| author
|
| ARLID |
cav_un_auth*0399069 |
| name1 |
La Cascia |
| name2 |
M. |
| country |
IT |
|
| source |
|
| source |
|
| cas_special |
| abstract
(eng) |
This study aims to propose a decision support system (DSS) for maintenance management of a service system, namely, a street cleaning service vehicle. Referring to the information flow management, the blockchain technology is integrated in the proposed DSS to assure data transparency and security. Design/methodology/approach: The DSS is designed to efficiently handle the data acquired by the network of sensors installed on selected system components and to support the maintenance management. The DSS supports the decision makers to select a subset of indicators (KPIs) by means of the Decision-Making Trial and Evaluation Laboratory method and to monitor the efficiency of performed preventive maintenance actions by using the mathematical model. Findings: The proposed maintenance model allows real-time decisions on interventions on each component based on the number of alerts given by sensors and taking into account the annual cost budget constraint. Research limitations/implications: The present paper aims to highlight the implications of the blockchain technology in the maintenance field, in particular to manage maintenance actions’ data related to service systems. Practical implications: The proposed approach represents a support in planning, executing and monitoring interventions by assuring the security of the managed data through a blockchain database. The implications regard the monitoring of the efficiency of preventive maintenance actions on the analysed components. Originality/value: A combined approach based on a multi-criteria decision method and a novel mathematical programming model is herein proposed to provide a DSS supporting the management of predictive maintenance policy. |
| result_subspec |
WOS |
| RIV |
JS |
| FORD0 |
20000 |
| FORD1 |
20300 |
| FORD2 |
20306 |
| reportyear |
2022 |
| num_of_auth |
7 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0322769 |
| confidential |
S |
| mrcbC91 |
C |
| mrcbT16-s |
0.417 |
| mrcbT16-E |
Q4 |
| arlyear |
2021 |
| mrcbU14 |
85089512877 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000564445500001 WOS |
| mrcbU63 |
cav_un_epca*0545773 Journal of Quality in Maintenance Engineering 1355-2511 1758-7832 Roč. 27 č. 4 2021 651 670 Emerald Publishing |
|