AI-Powered Industrial Automation: Trends and Challenges

Abstract

The introduction of Artificial Intelligence (AI) has greatly changed the nature of automation in industries making manufacturing processes smarter, efficient, and adapting. Industrial automation using AI makes use of machine learning (ML), deep learning (DL), computer vision and predictive analytics to streamline the production process, cut down on operational expenses, increase safety and quality. In this paper, we are going to take a look at the modern trends and uses and issues which are related to the integration of AI into industrial automation systems. Among the most important tendencies, there are autonomous robotics, predictive maintenance, AI-based quality control, and real-time process optimization. Another issue that the study recognizes potentially impacting the successful implementation of AI technologies is the issue of data security, system interoperability, workforce adaptation, and algorithm transparency. The results indicate that, although AI adoption can be highly beneficial in terms of productivity, efficiency, and decision-making, one should pay extra attention to the issue of data governance, human-machine cooperation, and the regulatory framework to implement AI sustainably.