A decision support system to assure high-performance maintenance service

• Published in: Journal of quality in maintenance engineering 2021-10, Vol.27 (4), p.651-670
• Main Authors: Aiello, Giuseppe, Benítez, Julio, Carpitella, Silvia, Certa, Antonella, Enea, Mario, Izquierdo, Joaquín, La Cascia, Marco
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Blockchain; Business metrics; Cryptography; Data acquisition; Data base management systems; Data integrity; Data transparency; Decision making; Decision support systems; Digital currencies; Digital signatures; Industry 4.0; Information flow; Information management; Information storage; Internet of Things; Maintenance management; Mathematical analysis; Mathematical models; Mathematical programming; Monitoring; Multiple criterion; Predictive maintenance; Preventive maintenance; Privacy; Security; Sensors; Street cleaning; Supply chain management
• ISSN: 1355-2511; 1758-7832
• DOI: 10.1108/JQME-11-2019-0107

PurposeThis 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/approachThe 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-MAaking Trial and Evaluation Laboratory method and to monitor the efficiency of performed preventive maintenance actions by using the mathematical model.FindingsThe 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/implicationsThe 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 implicationsThe 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/valueA 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.