Technologies That Power Smart Factories

As the demand for smarter, more connected systems continues to rise, PLCs are evolving beyond their traditional boundaries. What was once considered a rigid, low-level controller is now starting to behave more like a modern computer—bridging the gap between industrial automation and full-stack development. I experienced this first hand recently as I had a project where I needed to pull data from a third party system. The catch? The data was only accessible via a REST API. Instead of routing everything through a middleware PC, I implemented an HTTP GET request directly from the PLC. The response came back in JSON format, which I parsed on the controller to populate target parameters in real time—no external hardware or conversion layer needed. Today’s PLCs are capable of much more than deterministic scan cycles and I/O control. A lot of PLCs are adopting items we see in a regular software development setting: - HTTP requests can now be sent and received directly from many brands of controllers - JSON parsing is becoming supported across several PLC platforms - RESTful APIs can be integrated to communicate with cloud services or MES/ERP systems through PLCs - Secure communication over protocols like MQTT and OPC UA is becoming more common - File handling, string manipulation, and even structured object handling are part of the toolbox - Some platforms support object-oriented programming and event-driven architectures Why does this matter? Because the modern factory is no longer isolated—it’s part of a broader ecosystem. Smart manufacturing, Industry 4.0, and IIoT demand seamless data flow between machines, systems, and people. As system engineers, we’re entering an exciting time where the roles of industrial control and software development are blending. This shift opens up new possibilities, but it also means we must continue expanding our skill sets beyond traditional methods of PLC programming. P.S. the controller I used for those HTTP requests mentioned earlier was an AutomationDirect BRX Model PLC. #IndustrialAutomation #PLCs #IIoT #Industry40 #AutomationEngineering #SmartManufacturing #PLCProgramming #OTmeetsIT #ControlSystems #JSON #APIs #EdgeComputing

Edge computing is making a serious comeback in manufacturing—and it’s not just hype. We’ve seen the growing challenges around cloud computing, like unpredictable costs, latency, and lack of control. Edge computing is stepping in to change the game by bringing processing power on-site, right where the data is generated. (I know, I know - this is far from a new concept). Here’s why it matters: ⚡ Real-time data processing: critical for industries relying on AI-driven automation. 🔒 Data sovereignty: keep sensitive production data close, rather than sending it off to the cloud. 💸 Cost control: no unpredictable cloud bills. With edge computing, costs are often fixed and stable, making budgeting and planning significantly easier. But the real magic happens in specific scenarios: 📸 Machine vision at the edge: in manufacturing, real-time defect detection powered by AI means faster quality control, without the lag from cloud processing. 🤖 AI-driven closed-loop automation: think real-time adjustments to machinery, optimizing production lines on the fly based on instant feedback. With edge computing, these systems can self-regulate in real time, significantly reducing downtime and human error. 🏭 Industrial IoT (and the new AI + IoT / AIoT): where sensors, machines, and equipment generate massive amounts of data, edge computing enables instant analysis and decision-making, avoiding delays caused by sending all that data to a distant server. AI is being utilized at the edge (on-premise) to process data locally, allowing for real-time decision-making without reliance on external cloud services. This is essential in applications like machine vision, predictive maintenance, and autonomous systems, where latency must be minimized. In contrast, online providers like OpenAI offer cloud-based AI models that process vast amounts of data in centralized locations, ideal for applications requiring massive computational power, like large-scale language models or AI research. The key difference lies in speed and data control: edge computing enables immediate, localized processing, while cloud AI handles large-scale, remote tasks. #EdgeComputing #Manufacturing #AI #Automation #MachineVision #DataSovereignty #DigitalTransformation

🚀 The Future Is Here: Where AI, IoT, and Private 5G Collide We’re entering a new era where Artificial Intelligence, Internet of Things, and Private 5G are no longer siloed technologies—they’re converging to unlock groundbreaking use cases across industries. We at GXC see this more and more each day! Here’s what that convergence looks like in the real world: 🔧 Smart Manufacturing AI-driven quality control systems use high-res IoT camera data to detect defects in milliseconds—enabled by private 5G’s ultra-low latency and guaranteed throughput. 🚜 Precision Agriculture Autonomous tractors equipped with IoT sensors adjust in real time based on AI-analyzed soil and crop data, streamed over private 5G networks in remote fields without public coverage. 🏭 Industrial Safety & Compliance AI models analyze real-time video and sensor data to detect worker falls, gas leaks, or equipment anomalies—instant alerts powered by edge computing and private 5G connectivity. 🚚 Logistics & Warehousing AI-optimized robotic pickers and drones navigate warehouse floors using spatial IoT data. Private 5G ensures real-time coordination and zero interference in dense environments. 🎥 Security & Surveillance AI-powered video analytics over private 5G enable instant threat detection across large sites—like airports or stadiums—where traditional Wi-Fi fails to scale or secure. 🔐 The secret ingredient? Private 5G. It brings the performance, reliability, and security needed to move massive IoT data to AI models in real time—right at the edge. The convergence is not a trend—it's a competitive advantage. Those who adopt it early will lead their industries into the next decade. #AI #IoT #Private5G #EdgeComputing #SmartManufacturing #Industry40 #AutonomousOperations #Connectivity #DigitalTransformation #SmartFarming #LogisticsTech #AIoT

Gone are the days when the only way to know something was wrong with your machinery was the ominous clunking sound it made, or the smoke signals it sent up as a distress signal. In the traditional world of maintenance, these were the equivalent of a machine's cry for help, often leading to a mad dash of troubleshooting and repair, usually at the most inconvenient times. Today, we're witnessing a seismic shift in how maintenance is approached, thanks to the advent of Industry 4.0 technologies. This new era is characterized by a move from the reactive "𝐈𝐟 𝐢𝐭 𝐚𝐢𝐧'𝐭 𝐛𝐫𝐨𝐤𝐞, 𝐝𝐨𝐧'𝐭 𝐟𝐢𝐱 𝐢𝐭"  philosophy to a proactive "𝐋𝐞𝐭'𝐬 𝐟𝐢𝐱 𝐢𝐭 𝐛𝐞𝐟𝐨𝐫𝐞 𝐢𝐭 𝐛𝐫𝐞𝐚𝐤𝐬" mindset. This transformation is powered by a suite of digital tools that are changing the game for industries worldwide. 𝐓𝐡𝐫𝐞𝐞 𝐍𝐮𝐠𝐠𝐞𝐭𝐬 𝐨𝐟 𝐖𝐢𝐬𝐝𝐨𝐦 𝐟𝐨𝐫 𝐄𝐦𝐛𝐫𝐚𝐜𝐢𝐧𝐠 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐌𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞: 𝟏. 𝐌𝐚𝐤𝐞 𝐅𝐫𝐢𝐞𝐧𝐝𝐬 𝐰𝐢𝐭𝐡 𝐈𝐨𝐓 By outfitting your equipment with IoT sensors, you're essentially giving your machines a voice. These sensors can monitor everything from temperature fluctuations to vibration levels, providing a continuous stream of data that can be analyzed to predict potential issues before they escalate into major problems. It's like social networking for machines, where every post and status update helps you keep your operations running smoothly. 𝟐. 𝐓𝐫𝐮𝐬𝐭 𝐢𝐧 𝐭𝐡𝐞 𝐂𝐫𝐲𝐬𝐭𝐚𝐥 𝐁𝐚𝐥𝐥 𝐨𝐟 𝐀𝐈 By feeding the data collected from IoT sensors into AI algorithms, you can uncover patterns and predict failures before they happen. AI acts as the wise sage that reads tea leaves in the form of data points, offering insights that can guide your maintenance decisions. It's like having a fortune teller on your payroll, but instead of predicting vague life events, it provides specific insights on when to service your equipment. 𝟑. 𝐒𝐭𝐞𝐩 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐰𝐢𝐭𝐡 𝐌𝐢𝐱𝐞𝐝 𝐑𝐞𝐚𝐥𝐢𝐭𝐲 Using devices like the Microsoft HoloLens, technicians can see overlays of digital information on the physical machinery they're working on. This can include everything from step-by-step repair instructions to real-time data visualizations. It's like giving your maintenance team superhero goggles that provide them with x-ray vision and super intelligence, making them more efficient and reducing the risk of errors. ******************************************** • Follow #JeffWinterInsights to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

𝐁𝐫𝐢𝐝𝐠𝐢𝐧𝐠 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠: 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐈𝐨𝐓 𝐆𝐚𝐭𝐞𝐰𝐚𝐲𝐬 🌐 The boundary between Information Technology (IT) and Operational Technology (OT) has long hindered holistic industry operations. Industrial IoT gateways are the champions heralding change. ✨ 𝐒𝐧𝐚𝐩𝐬𝐡𝐨𝐭 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: - The IIoT gateway market surged ~14.7% within a year, nearing the $860 million mark, and this trajectory is predicted to continue through 2027. - Major players in this shift are Cisco, Siemens, Advantech, and MOXA. 🏭 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐄𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧: IIoT gateways are pivotal in reshaping the manufacturing landscape. By retrofitting even older systems, they facilitate real-time data exchange between operations and IT/cloud realms. This harmonization yields key outcomes: reduced downtimes (as illustrated by Vitesco's preemptive malfunction detection), significant labor cost reductions, and optimized energy use. The result? Streamlined operations, significant savings, and enhanced productivity. 🚀 🛠️ 𝐃𝐞𝐞𝐩 𝐃𝐢𝐯𝐞: 1) 𝑰𝑻/𝑶𝑻 𝑺𝒚𝒏𝒄𝒉𝒓𝒐𝒏𝒊𝒛𝒂𝒕𝒊𝒐𝒏: Legacy equipment, often disconnected, is now plugged into the digital grid. IIoT gateways serve as conduits, ensuring swift, seamless data transitions to IT platforms. 2) 𝑮𝒂𝒕𝒆𝒘𝒂𝒚 𝑭𝒓𝒂𝒎𝒆𝒘𝒐𝒓𝒌𝒔: They're not one-size-fits-all. Four distinct architectures accommodate diverse enterprise needs, ensuring smooth data flows and heightened efficiency. 3) 𝑽𝒆𝒓𝒔𝒂𝒕𝒊𝒍𝒊𝒕𝒚: Modern IIoT gateways juggle multiple roles - from protocol translation to security management, making them indispensable in a robust IIoT ecosystem. 💼 𝐅𝐮𝐫𝐭𝐡𝐞𝐫 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: 1) 𝑺𝒐𝒇𝒕𝒘𝒂𝒓𝒆 𝑴𝒊𝒈𝒓𝒂𝒕𝒊𝒐𝒏: Companies are transitioning key applications to the cloud, elevating IIoT gateways as primary data traffic controllers. 2) 𝑯𝒂𝒓𝒅𝒘𝒂𝒓𝒆 𝑬𝒗𝒐𝒍𝒖𝒕𝒊𝒐𝒏: Gateways now sport multi-core processors, AI chipsets, and enhanced security elements, ensuring swifter and safer data processing. 3) 𝑩𝒆𝒏𝒆𝒇𝒊𝒕: IIoT gateways have led to profound IT/OT integrations. Examples include Vitesco Technologies Italy's advanced malfunction prediction and Corpacero's reduced repair costs thanks to predictive maintenance. The once aspirational fusion of IT and OT is now tangible, courtesy of IIoT gateways. The forthcoming industrial epoch? Seamlessly integrated, vastly efficient, and pioneering. 🔍 Source: IoT Analytics (https://lnkd.in/euj3wiUD)

Your manufacturing plant is already talking. The question is—are you listening? Every second, your production line sends invisible signals: Where it's slowing down. Where energy is being wasted. Where a future bottleneck is quietly forming. When something breaks, you fix it. When output dips, you analyze it. When quality drops, you investigate it. But what if… You could see it coming before it ever happened? That’s exactly what the world’s smartest factories are doing. And no—it’s not luck. It’s Digital Twins. Here’s how they’re quietly winning: ✅ They simulate everything—before touching the floor. Using Discrete Event Simulation, they model thousands of “what-if” scenarios ahead of time. ✅ They test scalability virtually. No downtime. No wasted effort. Just pure clarity on what works at 10 units—or 10,000. ✅ They build feedback loops that self-correct. Production issues don’t surprise them—they notify them. ✅ They optimize resource flow in advance. Material, machine, and manpower aligned like clockwork—before the day begins. ✅ They plan for “what if” scenarios—before they happen. What if a supplier delays shipment? What if demand spikes overnight? What if a station fails? Digital Twins let you test it all—before it hits the floor. ✅ They validate line changes without stopping production. Need to rearrange stations or introduce a new variant? It’s simulated, validated, and tweaked—all before operators touch it. ✅ They make daily operations visual and data-driven. From shift supervisors to plant managers—everyone sees the same digital reality. No guesswork. No misalignment. Just clarity. This isn’t a pipe dream. This isn’t reserved for billion-dollar tech companies. This is now. This is Digital Twin Technology. It’s like giving your factory a second brain: • One that never sleeps • One that learns faster than humans • One that speaks in data, not guesses And the outcome? - Less waste - More throughput - Smarter decisions at every level I broke this approach down in a visual you can show your CEO, ops team, or even your board. One page. Clear. Actionable. - Digital Twins are your factory’s second brain ♻️ Repost if you're scaling smart.

The Missing Piece of Smart Things Manufacturing 🧠⚡ Remember our vision of 3D printing smart shipping boxes and supply chain sensors at any corner store earlier this week? One underlying technology that can make it possible are new chips that think like the human brain. Neuromorphic edge chips are now so small and efficient they can be embedded anywhere. We're talking tiny 1-milliwatt processors that work like our brains do—100x faster processing and 500x lower energy consumption. 🚀 Companies like BrainChip and SynSense are developing these today. While not ready for any old box yet, they're rapidly approaching the point where intelligence becomes as standard as plastic in manufacturing. What becomes possible when 1-milliwatt intelligence gets embedded anywhere? 💡 📦 Smart packaging on pallets that knows when something's wrong 🔐 Product-level monitoring with chips smart enough to detect issues 📊 Equipment sensors that understand their environment and alert you instantly ⚡ Connected intelligence in boxes, products, even intelligent documents Here's the breakthrough: 🎯 These chips literally work like our brains do—they only activate when something happens. Smart enough to understand when something's wrong, connected enough to let you know instantly. 🧠 Brain-inspired processing that mimics human neurons 🔋 1-milliwatt power - operates for months on minimal energy 💾 Microscopic size - getting small enough for embedding anywhere 💰 Incredible economics - intelligence approaching the cost of a sticker Imagine designing things by specifying not just shape and material, but exactly where to place micro-intelligence during printing. Every object emerges already smart, already connected. What becomes possible when intelligence is built into the manufacturing process? 🤔 The answer is reshaping entire industries—and we're just getting started. 🌍 #Innovation #3DPrinting #SmartObjects #SupplyChain #Logistics #Manufacturing #EdgeComputing #Neuromorphic

As headhunters, we are witnessing how leaders in the manufacturing industry are thriving in their decision-making under pressure by implementing the following recommendations: Embrace IoT for Predictive Maintenance: Implementing the Internet of Things (IoT) in manufacturing operations, as seen with General Electric, enables predictive maintenance, reducing downtime and enhancing efficiency. Utilize AI for Quality Control: Adopting Artificial Intelligence (AI) for tasks like quality control, like BMW's use of AI for assembly line analysis, leads to more accurate and faster decision-making processes. Leverage Big Data for Supply Chain Optimization: Companies like Cisco Systems demonstrate how big data can optimize supply chain management, allowing manufacturers to respond swiftly to changes and disruptions. Incorporate 3D Printing for Rapid Prototyping: Utilizing 3D printing technology, as Ford does, speeds up the prototyping process, enabling quicker decision-making and reducing time to market. Use Digital Twins for Testing and Simulation: As Siemens does, implementing digital twins for product and process simulation can significantly enhance decision-making efficiency and accuracy. Implement Real-Time Dashboards for Operational Insight: Integrating real-time dashboards, like Tesla, offers immediate operational insights, aiding faster and more informed decision-making. Adapt JIT Philosophy for SMEs: Small and Medium Enterprises (SMEs) should consider adopting Just-In-Time (JIT) strategies with adjustments for scale, as demonstrated by ABC Manufacturing, to enhance efficiency and responsiveness. Build Robust Local Supplier Networks: Like ABC Manufacturing, SMEs can benefit from developing strong local supplier relationships to reduce dependency and increase supply chain resilience. Adopt Flexible Production Strategies: Incorporating flexible production strategies allows companies to respond rapidly to market changes, a crucial aspect for SMEs in JIT implementation. Commit to Continuous Improvement and Feedback: As practiced by ABC Manufacturing, regular process reviews and incorporating feedback are essential for adapting and refining strategies and ensuring continuous improvement in decision-making processes. The following article provides a holistic approach to leaders’ decision-making under pressure in the manufacturing sector, emphasizing the importance of digital integration, agility, and strategic partnerships in navigating modern manufacturing challenges. #decisionmaking #topnotchfinders #sanfordrose

🚀 AI-Powered Industrial Revolution: How Rockwell Automation is Shaping the Future of Smart Manufacturing Artificial Intelligence and Generative AI are transforming industrial automation, and Rockwell Automation is at the forefront of this revolution. By embedding AI into manufacturing execution systems (MES), digital twins, industrial IoT, and supply chain optimization, Rockwell is unlocking new levels of efficiency, productivity, and resilience in industrial operations. 💡 Key AI Innovations by Rockwell Automation: ✅ Predictive Maintenance – AI-driven analytics reduce machine downtime and optimize performance. ✅ Generative AI for Industrial Design – AI automates engineering workflows, system design, and PLC programming. ✅ AI-Powered Industrial IoT (IIoT) – FactoryTalk InnovationSuite provides real-time monitoring and predictive insights. ✅ AI in Supply Chain Management – Intelligent forecasting, risk assessment, and logistics optimization. 🌍 The Bigger Picture: AI is driving autonomous manufacturing, edge computing, and human-machine collaboration, making industrial automation smarter, faster, and more resilient. Competitors like Siemens, ABB, Schneider Electric, and Honeywell are also investing in AI, but Rockwell’s integrated approach to AI-powered automation gives it a competitive edge. ⚠️ Challenges & Considerations: 🔹 AI model accuracy and reliability in critical industrial processes. 🔹 Cybersecurity risks in AI-driven industrial control systems. 🔹 Regulatory compliance with NIST, ISO, and the EU AI Act for AI governance. The future of industrial automation is AI-driven, autonomous, and adaptive. Rockwell Automation is shaping that future by blending AI, IoT, and automation to build the factories of tomorrow. 💬 What do you think about AI’s role in industrial automation? How do you see AI transforming manufacturing in the next decade? Drop your thoughts below! ⬇️ #AI #Automation #Industry40 #SmartManufacturing #RockwellAutomation #IndustrialAI

𝗜𝗺𝗮𝗴𝗶𝗻𝗲 𝗬𝗢𝗨𝗥 𝗳𝗮𝗰𝘁𝗼𝗿𝘆 𝘄𝗶𝘁𝗵: ✅ No more bulky fixtures ✅ No more reliance on mechanical guides ✅ Just AI-driven with real-time control My 𝗧𝗵𝘂𝗿𝘀𝗱𝗮𝘆 𝗧𝗵𝗼𝘂𝗴𝗵𝘁 explains how we use AI to ensure the correct bolting sequences on some critical operations. 🔩🤖 In most factories, tightening bolts in the correct sequence is critical to ensuring a secure assembly. Think about how you tighten the bolts on a wheel— you don’t go in a circle; you follow a zigzag pattern. Today, ensuring the bolting tool is in the correct position before activation requires 𝗹𝗮𝗿𝗴𝗲 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝗰𝗮𝗹 𝗳𝗶𝘅𝘁𝘂𝗿𝗲𝘀 𝘄𝗶𝘁𝗵 𝘀𝗲𝗻𝘀𝗼𝗿𝘀. These structures detect the tool’s X, Y, and Z coordinates, preventing it from turning on unless it’s precisely positioned. 𝗕𝘂𝘁 𝘄𝗵𝗮𝘁 𝗶𝗳 𝘄𝗲 𝗰𝗼𝘂𝗹𝗱 𝗲𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗲 𝘁𝗵𝗮𝘁 𝗺𝗲𝗰𝗵𝗮𝗻𝗶𝗰𝗮𝗹 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝗹𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿? That’s precisely what we’ve done using computer vision AI. Like self-driving cars that detect objects in 3D space, we use AI to track the bolting tool in real-time, identifying its exact location without any physical positioning sensors. 💡 The AI knows where the socket is, whether your hand is in the way, and when the tool is in the correct position—allowing the system to activate the bolting tool only at the right moment. But that’s not all. 𝗗𝗮𝘁𝗮 𝗯𝗶𝗮𝘀 plays a crucial role in AI training. If we train the model on one set of hands, it may struggle to recognise others. However, we can also use bias to our advantage — for instance, deliberately training AI to recognise only hands with gloves to enforce safety protocols. 🔎 This our future of precision manufacturing—replacing physical constraints with AI-driven intelligence. Explore more of our manufacturing innovations by checking out our previous videos here: https://lnkd.in/dU6aJ9s2 📢 Stay ahead of the latest in AI and automation—like and follow our page for more insights! #ThursdayThought #AIinManufacturing #ComputerVision #IndustrialAutomation #SmartFactories #DigitalTransformation #BiasInAI #BoltingSolutions #FactoryAutomation #Jendamark #Odin