A methodology to boost data-driven decision-making process for a modern maintenance practice

Maintenance is evolving due to the double-sided influence of the Asset Management paradigm and digitalization. In this evolution, assessing the maintenance management process status in terms of process completeness, information and data completeness and integration is paramount to boost reliable dat...

Full description

Saved in:
Bibliographic Details
Published inProduction planning & control Vol. 34; no. 14; pp. 1333 - 1349
Main Authors Polenghi, Adalberto, Roda, Irene, Macchi, Marco, Pozzetti, Alessandro
Format Journal Article
LanguageEnglish
Published London Taylor & Francis 26.10.2023
Taylor & Francis LLC
Subjects
Asset management
Automobile industry
Completeness
Data
data model
Data models
Decision making
Digitization
Information
maintenance
Maintenance management
Methodology
Methods
Online AccessGet full text

Cover

More Information
Summary:Maintenance is evolving due to the double-sided influence of the Asset Management paradigm and digitalization. In this evolution, assessing the maintenance management process status in terms of process completeness, information and data completeness and integration is paramount to boost reliable data-driven decision-making. Grounding on Design Science Research, a methodology is realized to favour the comparison of two data models, a reference one and a company-specific one, used as a means to evaluate the process status. In particular, the methodology embeds a reference data model for the maintenance management process. Both methodology and data model are artefacts tested and refined during action research in an automotive company willing to improve the maintenance management process. The application of both artefacts demonstrates that the company is facilitated in planning improvement actions for various time horizons to foster a modern maintenance practice whose decision-making is more data-driven.
ISSN:0953-7287
1366-5871
DOI:10.1080/09537287.2021.2010823