Utilizing Artificial Intelligence Predictive Maintenance in Lean Manufacturing to Boost Industrial Sustainability and Energy Efficiency
Year: 2025
Type: article
Study design: Systematic Review
Abstract: The implementation of Artificial Intelligence (AI)-driven Predictive Maintenance (AI-PdM) within Lean Manufacturing has emerged as a transformative strategy to improve energy efficiency and promote industrial sustainability. AI-PdM supports continuous condition monitoring, advanced predictive analytics, and optimized maintenance planning, which help mitigate unexpected downtimes, enhance equipment longevity, and maximize energy utilization. This research adopts a Systematic Literature Review (SLR) approach to evaluate AI-PdM’s impact on manufacturing efficiency and its correlation with Sustainable Development Goals (SDG) 7 (Affordable and Clean Energy) and SDG 9 (Industry, Innovation, and Infrastructure). The study’s findings highlight AI-PdM’s significant contribution to lowering carbon emissions, increasing operational dependability, and fostering sustainable production methods. Nevertheless, obstacles such as substantial initial capital requirements, a shortage of specialized workforce, and difficulties in integrating with existing systems continue to hinder its widespread adoption. Therefore, this paper advocates for the establishment of standardized guidelines and stronger collaboration among academia, industry stakeholders, and policymakers to accelerate AI-PdM adoption in sustainable manufacturing.
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7117693698
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