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AI-Enabled Automation Models for Next Generation Industrial Applications

Author(s) G. Ayorkor Korsah
Country Ghana
Abstract The rapid evolution of industrial technologies has accelerated the transition from conventional automation toward intelligent, adaptive, and data-driven manufacturing environments. Artificial intelligence has emerged as a critical technological component of this transformation by enabling industrial systems to analyze operational data, recognize patterns, predict system behavior, and support autonomous decision-making. This study examines AI-enabled automation models for next-generation industrial applications and proposes an integrated conceptual framework for intelligent industrial operations. The research adopts a conceptual and descriptive design based on secondary literature concerning artificial intelligence, machine learning, industrial automation, robotics, predictive maintenance, intelligent manufacturing, digital twins, and industrial Internet of Things technologies.
The proposed model integrates industrial data acquisition, preprocessing, AI-based analysis, intelligent decision-making, automated execution, performance monitoring, and continuous learning. The analysis indicates that AI-enabled automation can improve production efficiency, equipment reliability, quality control, resource utilization, operational flexibility, and real-time responsiveness. However, challenges related to data quality, cybersecurity, workforce adaptation, system interoperability, computational requirements, explainability, and implementation costs remain significant. The study concludes that AI-enabled automation can provide a strong technological foundation for next-generation industrial systems by combining intelligent prediction with autonomous operational control. Effective implementation requires scalable architectures, reliable data infrastructures, continuous monitoring, and appropriate human oversight.
Keywords Artificial Intelligence, Industrial Automation, Intelligent Manufacturing, Machine Learning, Smart Industry, Predictive Maintenance, Industrial Robotics, Digital Transformation.
Field Engineering
Published In Volume 1, Issue 2, March-April 2019
Published On 2019-04-14
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