Towards Predictive Maintenance 5.0: Life Cycle Sustainability Assessment of Enabling Technologies
Year: 2026
Type: conference-paper
Abstract: Predictive maintenance (PdM) is a key component of digital manufacturing and can be supported by digital technologies such as Internet of Things and Artificial Intelligence. Although PdM can improve maintenance performance and asset reliability, its sustainability implications remain insufficiently addressed. In particular, the environmental, economic, and social impacts associated with the hardware and digital infrastructure supporting PdM are often overlooked. Motivated by these challenges, this paper proposes a life cycle sustainability assessment framework for AI-based PdM. This framework focuses specifically on the environmental and economic dimensions of sustainability, with particular attention to the hardware supporting AI-based PdM, and structures the assessment across relevant life cycle stages, from production to end of life. By providing a consistent basis for analyzing sustainability trade-offs alongside PdM performance, this work provides a structured methodological foundation and is a first step toward Maintenance 5.0 through the integration of sustainability considerations into digital maintenance decision-making.
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7203601946