Most factories already collect oceans of data, yet too much of it arrives in different shapes, names, and units. That inconsistency slows down Artificial Intelligence (AI) projects more than any model choice. During AI Frontiers 2025, a participant asked whether the Asset Administrative Shell could help manufacturers tame this variability and make data usable for […]
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Manufacturing floors across many industries are often powered by decades-old machinery. This legacy equipment is reliable, but it presents a significant challenge: the original design data is frequently missing, incomplete, or outdated.How do you maintain, repair, or improve an asset when its design drawings are nowhere to be found? This is where reverse engineering, supercharged […]
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Walk any production line and you’ll see the same truth: decisions live on the human–machine interfaces (HMIs) that operators watch all day. If you want agentic AI to help now—not after a multiyear overhaul—start there. Let the assistant read what your people already read: HMIs and SCADA views, historian trends, shift notes, test logs, and […]
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Picture a line drifting off spec at midnight. Operators don’t want a chatbot—they need a system that notices the issue, understands the context, and recommends an action they can trust. That trust isn’t created at the moment of the alert; it’s built weeks earlier in how you prepare your data, systems, and people. During “Agentic […]
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When people hear “digital transformation,” many picture massive factories with endless budgets and global IT teams. But the reality is that the future of U.S. manufacturing depends on much smaller companies. According to the SBA, nearly 98% of all manufacturers fall into the “small business” category. For them, transformation isn’t about getting ahead—it’s about staying […]
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Answering an AI Frontiers 2025 audience questionContext. During AI Frontiers 2025, an attendee asked: Who should be the business owner and senior stakeholder for an AI proof of concept—and how should it be structured for quick wins and long-term scale? This article distills the panel’s answer from “Building Data Accuracy and AI Trust in Smart Manufacturing.” Want to check the on-demand […]
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Walk into many sheet metal shops today, and you’ll still find one of the most critical workflows running on a surprisingly fragile medium: paper. Job travellers, or the packets of instructions that follow a part from cutting to bending to finishing, remain the backbone of production in thousands of fabrication plants worldwide.But as manufacturers across […]
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Small and mid-size manufacturers often ask: Is agentic AI truly within our reach, or is it a luxury only global plants can afford? At the “Agentic AI in Manufacturing: From Copilots to Autonomous Systems” session during AI Frontiers 2025, organized by IIoT World, panelists from AstraZeneca, Cybus, Infinite Uptime, and Frost & Sullivan shared practical guidance. Their […]
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How a coordinated team of AI agents tackles everyday pain points across planning, scheduling, reliability, and feedback AI in maintenance isn’t always about robots taking decisions or futuristic predictions. AI can also take on a very practical role in maintenance: acting as a full maintenance team of AI agents that quietly handles the everyday points […]
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Answering the audience’s questions At the AI Frontiers 2025 event, one audience member posed a question that goes to the heart of modern manufacturing challenges: “When introducing agentic AI into domain-specific workflows, what best practices help manufacturers improve product quality and decision-making speed while minimizing operational risk, especially in highly regulated or safety-critical industries?” A panel of […]
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Answering the AI Frontiers Audience’s Question“Generative AI isn’t just about documents. Factories generate huge amounts of sensor data, but turning that into real value with AI is challenging. What should companies tackle first—improving data quality, linking older systems, training teams, or meeting regulatory requirements? And how can they set priorities to get quick results while […]
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Midnight on a production line isn’t the time for a generic alert. When a critical asset starts drifting, teams don’t want a chatbot—they need a specific diagnosis and a plan they can run safely, with the parts and people they actually have on hand. That’s the gap between “detect” and “do,” and it’s where the […]
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