A review of artificial intelligence applications in manufacturing operations

Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, sustainability. However, using AI in also presents several challenges, including issues with data acquisition management, human resources, infrastructure, as well security risks, trust, implementation challenges. For example, getting the needed to train models be difficult for rare events or costly large datasets that need labeling. pose risks when integrated into industrial control systems. In addition, some industry players may hesitant use due a lack of trust understanding how it works. Despite these has potential extremely helpful manufacturing, particularly applications such predictive maintenance, quality assurance, process optimization. It is important consider specific needs capabilities each scenario deciding whether manufacturing. This review identifies current developments, future directions AI/ML relevant goal improving technologies available solving problems, providing decision-support prioritizing selecting appropriate technologies, identifying areas where further research yield transformational returns industry. Early experience suggests have significant cost efficiency benefits especially combined ability capture enormous amounts from