Published Online:February 2025
Product Name:The IUP Journal of Mechanical Engineering
Product Type:Article
Product Code:IJME010225
DOI:10.71329/IUPJMECH/2025.18.1.7-31
Author Name:Attia Hussien Gomaa
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:7-31
Smart maintenance in Industry 4.0 is reshaping asset management by integrating cyber-physical systems, real-time data analytics and advanced optimization methodologies to enable predictive, autonomous and efficient maintenance strategies. In this context, the integration of Digital Twins (DTs) and Lean Six Sigma (LSS) presents a powerful approach for optimizing proactive maintenance efforts. DTs create dynamic digital replicas of physical assets, providing real-time monitoring, predictive diagnostics, and scenario-based simulations, while LSS focuses on reducing process variability and improving efficiency. Despite their individual benefits, the combined potential for enhancing maintenance management remains underexplored. This paper investigates the synergistic integration of DTs and LSS, proposing a comprehensive framework for improving predictive maintenance, decision-making accuracy, and operational efficiency. By analyzing existing literature and identifying key challenges, the study outlines a strategic roadmap for achieving maintenance excellence, minimizing downtime, and maximizing asset performance within Industry 4.0. The findings offer valuable insights for industry professionals and researchers seeking to leverage digital transformation and data-driven methodologies to advance smart manufacturing and elevate maintenance practices in the digital age.
Smart maintenance in Industry 4.0 leverages real-time analytics and optimization to drive predictive and autonomous maintenance, enhancing operational efficiency.