Editorial for the Special Issue on Sustainable Maintenance 4.0

It is our great pleasure to introduce this Special Issue on “Sustainable Maintenance 4.0” in the International Journal of Prognostics and Health Management (IJPHM). This Special Issue addresses a timely and strategic shift in maintenance engineering and Prognostics and Health Management (PHM): the transition toward maintenance strategies that are not only efficient and reliable, but also environmentally responsible, resource-aware, and socially sustainable.Global challenges such as climate change, resource depletion, and growing expectations for industrial responsibility call for a transformation of maintenance practices. Although maintenance strongly influences environmental and social performance, these dimensions remain underexplored in current research. Meanwhile, the rise of Industry 4.0/5.0—through digitalization, automation, AI, big-data analytics, and predictive maintenance—offers powerful opportunities to enhance sustainability, optimize resource use, reduce waste, and extend asset lifetime. These technologies also support the development of new sustainability-oriented KPIs that go beyond traditional economic indicators.The contributions collected in this issue illustrate this evolution and provide new insights for both researchers and practitioners.

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Publication Details

Journal
International Journal of Prognostics and Health Management
Published
2025-11-14
DOI
https://doi.org/10.36001/ijphm.2025.v16i4.4703
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
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article

Editorial for the Special Issue on Sustainable Maintenance 4.0

Olivier Sénéchal, Lucas Equeter, Phuc Do
International Journal of Prognostics and Health Management
Machine Fault Diagnosis Techniques
article

Editorial for the Special Issue on Sustainable Maintenance 4.0

Olivier Sénéchal, Lucas Equeter, Phuc Do
article en

Abstract

It is our great pleasure to introduce this Special Issue on “Sustainable Maintenance 4.0” in the International Journal of Prognostics and Health Management (IJPHM). This Special Issue addresses a timely and strategic shift in maintenance engineering and Prognostics and Health Management (PHM): the transition toward maintenance strategies that are not only efficient and reliable, but also environmentally responsible, resource-aware, and socially sustainable.Global challenges such as climate change, resource depletion, and growing expectations for industrial responsibility call for a transformation of maintenance practices. Although maintenance strongly influences environmental and social performance, these dimensions remain underexplored in current research. Meanwhile, the rise of Industry 4.0/5.0—through digitalization, automation, AI, big-data analytics, and predictive maintenance—offers powerful opportunities to enhance sustainability, optimize resource use, reduce waste, and extend asset lifetime. These technologies also support the development of new sustainability-oriented KPIs that go beyond traditional economic indicators.The contributions collected in this issue illustrate this evolution and provide new insights for both researchers and practitioners.

International Journal of Prognostics and Health ManagementVol. 16(4)
University of Mons (BE), IMT Mines Alès (FR), Université Polytechnique Hauts-de-France (FR)
Openalex Percentile: Top 57%
Machine Fault Diagnosis Techniques
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