Understanding where AI fits within industrial automation will help to leverage its potential effectively.
Automation engineers should take note of the practical applications and limitations of AI in industrial settings, particularly large language models (LLMs) and multimodal AI, Control reported in a recent article.
While LLMs excel at processing and summarizing text data, they lack analytical reasoning and consistency, making them unsuitable for control logic or mission-critical decision-making. However, the emergence of multimodal AI presents promising opportunities, especially in maintenance and inspection tasks.
These models can analyze images from drones or ground-level inspections to identify corrosion, leaks and structural anomalies, reducing the burden on human inspectors. When combined with historical data and asset tracking, AI-driven visual analysis can enhance preventive maintenance and streamline work orders, improving plant reliability and efficiency.
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