| dc.description.abstract | This study examines the transformative impact of artificial intelligence (AI) on manufacturing, highlighting its role in enhancing productivity, efficiency, and sustainability. It traces the evolution from traditional manufacturing methods through Industry 4.0 to the emerging Industry 5.0 paradigm, emphasizing AI's integration with cyber-physical systems, digital twins, and advanced robotics. Key applications such as predictive maintenance, process optimization, supply chain management, and energy efficiency are analyzed for their economic and environmental benefits. The research addresses challenges including interoperability, scalability, data quality, and workforce adaptation, with particular attention to the implications for small and medium enterprises and the broader labor market. Ethical considerations, regulatory compliance, and public acceptance are explored to ensure responsible AI deployment. The paper also discusses future trends, including explainable AI, edge computing, autonomous decision-making, and the convergence of AI with additive manufacturing and blockchain technologies. Strategic roadmaps for phased AI adoption are proposed to guide manufacturing organizations in achieving competitive advantage while aligning with sustainability and human-centric principles. Overall, the work provides a comprehensive framework for understanding AI-driven industrial transformation and its multifaceted impacts on economic performance, workforce dynamics, and environmental stewardship.
Keywords: Smart Manufacturing, Industry 4.0, Artificial Intelligence in Manufacturing, Digital Twin, Predictive Maintenance, Sustainable Manufacturing, Human-AI Collaboration, Circular Economy, Explainable AI (XAI), Cyber-Physical Systems (CPS) | en_US |
