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.
Authors
- Olivier Sénéchal
- Lucas Equeter (ORCID: https://orcid.org/0000-0003-0442-8015)
- Phuc Do
Institutions
- University of Mons (BE)
- IMT Mines Alès (FR)
- Université Polytechnique Hauts-de-France (FR)
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
- 0.00