A decision support system to assure high-performance maintenance service

Antonella Certa, Giuseppe Aiello, Mario Enea, Marco La Cascia, Silvia Carpitella, Silvia Carpitella, Joaquín Izquierdo, Julio Benítez

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: 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-MAaking 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. © 2020, Emerald Publishing Limited.
Original languageEnglish
Number of pages20
JournalJournal of Quality in Maintenance Engineering
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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