People of Packaging · 12 Sept 2024 · 13m
Steve Lynn, Director of Labels and Packaging for Durst North America, discusses Durst's evolution in digital inkjet printing and its strategic partnership with Omet to create hybrid label presses. He highlights the company's shift to 1200 DPI resolution and the introduction of Hawk AI, an AI-driven quality control system that inspects prints and makes real-time corrections to reduce waste and operator dependency. Lynn also details the press's versatility in handling various materials, including pressure-sensitive labels, shrink sleeves, and in-mold labels, while emphasizing the role of Durst Analytics in monitoring press performance.
Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.
ManufacturingHawk AI
An AI-powered camera system inspects printed images at full speed to detect defects like misregistration or color shifts and makes instant corrections on the fly without operator intervention.
“Hawk AI, which is a camera system that's using artificial intelligence, to look at printed images, inspect them, and make corrections, to keep print quality in perfect condition at full speed on the fly with no operator intervention.”
Speaker 2 · Hear it at 6:55
established companies
Other shows on the same ground, closest first.
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Daniel First, founder and CEO of Axion, explains how AI is transforming quality and innovation roles in manufacturing by turning overwhelming streams of customer, device, and service data into actionable insights. He argues that quality teams are shifting from plant-floor oversight to strategic partners across engineering, marketing, and supply chain, using AI to accelerate product evolution and break down silos. First highlights specific examples, such as Shark Ninja’s ice cream machine and power systems in mines, to illustrate how unexpected customer usage drives innovation and how AI agents can detect root causes faster than humans.
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Scott Everett, Co-Founder and CEO of Eigen Innovations, explains how his company uses industrial vision systems and AI to transform manufacturing quality control from reactive, destructive testing to proactive, insight-driven decision-making. He argues that while IoT infrastructure for data capture is mature, the industry struggles with 'insight architecture,' requiring contextualized data to provide explainable stories that empower non-technical operators to make real-time adjustments. Everett highlights specific applications in the automotive sector, such as ensuring the hermetic seal of vehicle headlights, where 100% inline inspection replaces random sampling to achieve zero-defect manufacturing.
Eythor Eiriksson, founder and CEO of euler, explains how his company uses AI to analyze existing powder bed fusion camera data for real-time monitoring and quality assurance in additive manufacturing. He details the platform's ability to predict defects like spatter and warping before they cause crashes, allowing operators to intervene early. Eiriksson discusses the challenges of data access for training models, the company's hybrid cloud/on-prem deployment strategy, and the future potential of reducing reliance on post-print CT scans.
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