AI without the BS: Evolve Your Automation and Engineering Capabilities with ML and GenAI

Everyone is scrambling to chart an AI and machine learning (ML) course and use cases for AI in industrial automation is no exception.

This FAQ helps cut to the chase, providing insights into AI adoption in manufacturing transformation. Some highlights:

Process optimization is a sweet spot. AI-driven process optimization is already having a significant impact. Instead of writing extensive code to explicitly direct a static operation, AI/ML models tap into learned behavior to optimize and automate processes based on specific conditions and thresholds. AI/ML models can also generate a more complete data set for process optimizations when existing algorithms aren’t available.

Boosting quality control. Industrial machine vision with AI/ML facilitates inspection results by training models for quality inspection as opposed to traditional manual vision inspections, which are highly labor-intensive.

Generative AI shows promise. Generative AI for engineering tools enhances productivity by synthesizing data sets, streamlining and automating tasks, and enabling faster analysis.

Data remains an inhibitor. AI/ML requires a lot of data to feed the models, and most industrial organizations are still behind the curve on data management strategies.

Download this FAQ to learn more about AI/ML in industrial automation along with how to advance the journey.

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