What do we understand under the term AI in Industrial Automation?

Artificial Intelligence (AI) is a broad term describing machines that can perform tasks normally requiring human intelligence. In industrial automation, AI helps systems make smarter decisions, adapt to changing conditions, and work more efficiently. To understand AI better, it helps to break it into three commonly used categories: machine learning, machine vision, and large language models (LLMs).

Machine Learning — Learning From Experience

Machine learning (ML) is the part of AI that allows computers to learn from data. Instead of being explicitly programmed for every rule, the system discovers patterns on its own.

Analogy: ML is like human learning — the more examples you see, the better you understand and predict.

Common industrial uses:

• Predictive maintenance (detecting failures before they happen)
• Anomaly detection in sensor data
• Optimization of energy or production parameters
• Quality prediction based on historical process data

Machine Vision — The Eyes of Automation

Machine vision enables computers to “see.” Using cameras and algorithms, it identifies objects, checks quality, or guides robots.

Analogy: Machine vision is like human eyesight — observing, recognizing, and evaluating visual information.

Common industrial uses:

• Visual quality inspection (scratches, defects, completeness)
• Robot guidance (picking, placing, alignment)
• Safety monitoring (detecting intrusions or unsafe conditions)

Large Language Models (LLMs) — Understanding and Communicating

Large Language Models are AI systems trained on vast amounts of text. They can understand questions, generate explanations, summarize information, or interact in natural language.

Analogy: LLMs are like the communication and reasoning part of the brain — interpreting context, answering questions, and giving suggestions.

Common industrial uses:

• Operator assistants (“AI copilots”) for troubleshooting
• Automated reporting and documentation
• Intelligent search in manuals and procedures
• Chat-based interfaces for SCADA, MES, or maintenance systems

Putting It All Together in Industry

Modern factories often blend these AI technologies:

• Machine vision checks product quality
• Machine learning predicts machine failures
• LLMs help technicians quickly find solutions or generate reports
• Together, they create more reliable, efficient, and flexible production systems