Daniel

Yes. AI is going to change PLC-based automation significantly, but I would not recommend replacing the PLC with an AI model. The better architecture is PLC + Edge AI, where the PLC continues to handle deterministic control and safety while AI handles prediction, optimization, anomaly detection and vision. Current industrial architectures already follow this approach: Siemens, for example, runs AI inference at the industrial edge and connects it to PLCs, drives, cameras and other automation equipment. (Siemens) How AI will change PLCs Traditional PLC AI-Augmented PLC Fixed logic and rules Learns patterns from machine data Reactive maintenance Predictive maintenance Fixed process parameters AI-assisted optimization Sensor-based inspection AI vision inspection Alarms after abnormality Early anomaly prediction Engineer investigates faults AI assists with root-cause analysis Manual optimization Continuous optimization PLC controls machine PLC controls + AI advises/optimizes 1. Predictive maintenance Instead of waiting for a motor, pump, bearing or conveyor to fail, AI can analyze temperature, vibration, current, pressure, speed and PLC alarm history to identify abnormal behavior. The PLC continues controlling the machine, while an AI model can calculate an anomaly score or estimate remaining useful life. Edge-based implementations can do this locally without sending all machine data to the cloud. (seco.com) 2. AI-based machine vision This is probably one of the most practical applications today. A camera can use an AI vision model to detect: Product defects Missing components Incorrect assembly Position/orientation Packaging problems Foreign objects The AI system then sends a simple result to the PLC, such as PASS / FAIL / DEFECT, and the PLC executes the required machine action. Siemens has already demonstrated this architecture with AI vision running locally and sending results to an S7-1500 PLC. (Siemens) 3. Intelligent process optimization AI can analyze historical production data and recommend better: Temperature settings Pressure Motor speed Flow rates Cycle times Energy consumption Production parameters This moves PLC automation from "execute predefined instructions" toward "execute instructions while continuously receiving intelligent recommendations." What AI model should you choose? There isn't one "best AI model" for PLCs. The model should be selected according to the use case. Requirement Recommended AI approach Predictive maintenance Time-series ML / anomaly detection Sensor anomaly detection Autoencoder, Isolation Forest, XGBoost Quality inspection CNN / Vision Transformer Forecasting LSTM, Temporal models, Gradient Boosting Process optimization Reinforcement Learning / optimization models Engineer assistance LLM PLC programming assistance Industrial LLM + engineering knowledge/RAG Operator chatbot LLM + plant data/RAG Real-time edge inference Small optimized ML model My recommendation for a new PLC + AI architecture For an industrial project in 2026, I would use: PLC → Industrial Edge Computer → AI Model → PLC The PLC remains responsible for real-time control, interlocks and safety. AI operates as an intelligence layer rather than replacing the deterministic control layer. This hybrid architecture is also consistent with current industrial AI approaches. (IPCS GLOBAL) For the AI model, I would choose differently depending on the objective: Predictive maintenance: XGBoost/LightGBM or an appropriate time-series/anomaly model Vision inspection: CNN/YOLO-class vision model or Vision Transformer Plant/operator assistant: a strong LLM connected through RAG to PLC documentation, alarms, manuals and historian data Advanced optimization: reinforcement learning or mathematical optimization, with strict safety constraints One important point: don't put an LLM directly in the PLC control loop. An LLM is excellent for understanding alarms, documentation, troubleshooting and operator interaction, but deterministic PLC logic should remain responsible for safety-critical machine control. So, if I were designing a new Siemens/Schneider/Rockwell PLC system today, I would not ask "Which AI PLC should I buy?" I would ask: "Which PLC + Edge AI architecture gives me deterministic control, local AI inference, secure data access and the ability to add new AI models later?" That approach gives you a much more future-proof automation platform.

Which PLC Is the Best These Days? A 2026 Comparison Programmable Logic Controllers (PLCs) remain at the heart of modern industrial automation, controlling everything from manufacturing lines and packaging machines to water treatment, power systems and process plants. In 2026, there is no single PLC that is best for every application. The right choice depends on performance, communication protocols, scalability, programming environment, safety requirements, existing infrastructure and local technical support. Among the leading platforms today are Siemens SIMATIC S7-1500, Rockwell Automation Allen-Bradley ControlLogix, Schneider Electric Modicon M580, Mitsubishi MELSEC iQ-R and Beckhoff CX. Industry comparisons continue to identify these platforms among the leading high-performance PLC choices. Siemens S7-1500 – Best Overall Choice For many new industrial automation projects, Siemens S7-1500 is arguably the strongest all-round choice. It offers scalable CPUs, integrated motion capabilities, extensive diagnostics, distributed I/O and strong PROFINET integration. Siemens also positions the S7-1500 as a high-performance and future-oriented automation platform with OPC UA capabilities. Its major advantage is the TIA Portal engineering environment, which brings PLC, HMI, drives and safety engineering together. This makes Siemens particularly attractive for large and complex automation projects. Rockwell ControlLogix – Best for North America Allen-Bradley ControlLogix remains an excellent option, particularly in North American facilities. Its strong EtherNet/IP ecosystem, extensive installed base and integration with Rockwell's automation portfolio make it a natural choice for organizations already using Allen-Bradley equipment. Schneider Modicon M580 – Best for Process and Infrastructure The Modicon M580 is a particularly strong choice for process industries, utilities and infrastructure. Its Ethernet-based architecture, redundancy options, cybersecurity features and integration with EcoStruxure make it suitable for large and highly available systems. Schneider also supports safety and redundant controller configurations on the M580 platform. Mitsubishi iQ-R and Beckhoff CX Mitsubishi MELSEC iQ-R is a strong option for high-speed manufacturing, motion and Asian industrial markets. Beckhoff CX, meanwhile, is attractive for Industry 4.0 and PC-based automation, particularly where EtherCAT and advanced IT/OT integration are important. PLC Comparison Table PLC Platform Best For Programming Main Network Key Strength Siemens S7-1500 General industrial automation TIA Portal PROFINET Overall performance & integration Rockwell ControlLogix North American plants Studio 5000 EtherNet/IP Ecosystem & reliability Schneider M580 Process, utilities & infrastructure EcoStruxure Control Expert Ethernet/Modbus TCP Redundancy & open Ethernet architecture Mitsubishi iQ-R High-speed manufacturing GX Works3 CC-Link IE Speed & motion Beckhoff CX Industry 4.0 & advanced automation TwinCAT 3 EtherCAT PC-based flexibility Final Verdict If you are starting a new general-purpose industrial automation project in 2026, the Siemens S7-1500 is one of the best overall choices because of its performance, scalability, engineering ecosystem and broad industrial adoption. However, the best PLC should always be selected according to the application. Choose ControlLogix for an Allen-Bradley/EtherNet/IP environment, M580 for process and infrastructure applications, Mitsubishi iQ-R for high-speed Asian manufacturing environments, and Beckhoff CX for highly flexible PC-based and Industry 4.0 systems. The most important point is that PLC selection is a long-term infrastructure decision. Existing engineering skills, spare-parts availability, integrator support and compatibility with your current automation network can be just as important as processor performance.