Year: 2025
Type: article
Abstract: Predictive maintenance (PdM) represents a vital operational tool that helps industries reduce their operational disruptions and lengthen equipment runtimes while reducing waste accumulation. Through PdM organizations gain environmental sustainability benefits through fewer energy requirements and decreased material losses and reduced emissions of greenhouse gases (GHG). The environmental effects of predictive maintenance receive thorough examination in this work based on literature research alongside case examples and confirmed data sources. Toxicological preservation benefits greatly from PdM because it enhances industrial waste reduction and sustainable energy usage and minimizes carbon emissions. The paper analyzes how AI along with IoT technology and big data analytics contribute to PdM effectiveness for sustaining industrial operations. The study highlights that despite the present implementation expenses and technical integration barriers initial PdM adopts various sustainable and operational strategies proven to be practical for environmental footprint reduction. Researchers should explore new paths that will show how predictive maintenance teams up with green technologies to achieve sustainable industrial changes in future work.
Author: Amit Saxena
Institution: Bellevue University
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409194538