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Data-based decision-making in maintenance service delivery: the D3M framework
University of Bergamo, ITA. (CESL)ORCID iD: 0000-0001-7671-6927
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.ORCID iD: 0000-0002-5076-3300
University of Bergamo, ITA. (CESL)ORCID iD: 0000-0003-4633-7568
University of Bergamo, ITA. (CELS)ORCID iD: 0000-0001-7983-8356
2021 (English)In: International Journal of Manufacturing Technology and Management (IJMTM), ISSN 1368-2148, E-ISSN 1741-5195, Vol. 32, no 9, p. 122-141Article in journal (Refereed) Published
Abstract [en]

Purpose – This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.

Design/methodology/approach – The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.

Findings – The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies’ necessities.

Originality/value – The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2021. Vol. 32, no 9, p. 122-141
Keywords [en]
Maintenance, Decision-making, Continuous improvement, Service operations, Servitization
National Category
Other Mechanical Engineering
Research subject
Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-21427DOI: 10.1108/JMTM-08-2020-0301ISI: 000761724400001OAI: oai:DiVA.org:bth-21427DiVA, id: diva2:1557733
Part of project
Model Driven Development and Decision Support – MD3S, Knowledge Foundation
Funder
Knowledge Foundation, 20180159
Note

open access

Available from: 2021-05-27 Created: 2021-05-27 Last updated: 2022-03-25Bibliographically approved

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Bertoni, Marco

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