AI in Industrial Automation: Where It Actually Adds Value
AI is most useful in a plant when it reduces uncertainty around a real engineering decision. Start with the decision, not the algorithm.
Read →Applied AI, machine learning, LLMs, computer vision and intelligent manufacturing.
AI is most useful in a plant when it reduces uncertainty around a real engineering decision. Start with the decision, not the algorithm.
Read →Large language models are excellent at language and weak at being treated as a control authority. In OT, that distinction is non-negotiable.
Read →Industrial organizations often have the right answer somewhere in a repository and still cannot find it quickly.
Read →Traditional alarms are good at detecting defined conditions. AI is useful when the interesting condition is a change in pattern.
Read →Predictive maintenance often fails because the organization has data, but not the data needed to answer the maintenance question.
Read →Edge AI is attractive when data is already close to the machine and the engineering constraints favor local processing.
Read →A production vision system is not just a model. Lighting, optics, mechanics and data quality determine whether the inspection works.
Read →MES already has production context. AI becomes useful when it helps people make better decisions without replacing the manufacturing system of record.
Read →AI can reduce the volume of security information an analyst must read, but OT actions still need controlled procedures.
Read →A digital twin is valuable when it helps engineers reason about a real system. AI can add learning and estimation without turning the twin into…
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