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 →AI
Industrial AI, machine learning, LLMs, agents, computer vision and applied engineering.
LLMs in OT: Why They Belong Beside the Control System, Not Inside It
Large language models are excellent at language and weak at being treated as a control authority. In OT, that distinction is non-negotiable.
Read →Retrieval-Augmented Generation for Industrial Documentation
Industrial organizations often have the right answer somewhere in a repository and still cannot find it quickly.
Read →Anomaly Detection vs. Traditional Alarms: What Should AI Actually Do?
Traditional alarms are good at detecting defined conditions. AI is useful when the interesting condition is a change in pattern.
Read →Predictive Maintenance: The Data Problem Engineers Underestimate
Predictive maintenance often fails because the organization has data, but not the data needed to answer the maintenance question.
Read →Edge AI in Manufacturing: When the Cloud Is the Wrong Place
Edge AI is attractive when data is already close to the machine and the engineering constraints favor local processing.
Read →Computer Vision for Quality Inspection: From Demo to Production
A production vision system is not just a model. Lighting, optics, mechanics and data quality determine whether the inspection works.
Read →AI + MES: Turning Production Data into Better Decisions
MES already has production context. AI becomes useful when it helps people make better decisions without replacing the manufacturing system of record.
Read →AI-Assisted OT Cybersecurity: Useful Patterns and Dangerous Ones
AI can reduce the volume of security information an analyst must read, but OT actions still need controlled procedures.
Read →Digital Twins + AI: Where Simulation Becomes Operationally Useful
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 a visual…
Read →The Practical AI Toolbox for Automation Engineers
Automation engineers do not need to become full-time data scientists to benefit from AI.
Read →How to Start an Industrial AI Project from Zero
A useful industrial AI project can start small. It needs a narrow question, measurable value and disciplined execution.
Read →