People of Packaging · 13 Sept 2024 · 22m
Jan de Roeck, Marketing Director for Industry Relations and Strategy at Esko, discusses how the company is using AI to automate pre-press workflows and solve inefficiencies in the label and packaging industry. He highlights 'Phoenix,' an AI tool that optimizes label layouts for efficiency, and prototypes for reverse-engineering color profiles and calculating carbon footprints. De Roeck explains that these innovations address the industry's shift toward shorter print runs driven by changing consumer behaviors and the demand for sustainable, transparent packaging.
Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.
Engineering & simulationPhoenix
Esko's Phoenix product uses AI algorithms to automatically calculate and organize multiple label design layouts on a single web or sheet to maximize efficiency based on variables like run length, substrate, and color count.
“Phoenix is using artificial intelligence to almost continuously calculate different options in terms of layouts and organizing them in function of which one is the most efficient one.”
Speaker 2 · Hear it at 14:07
Engineering & simulationEsko prototype (developed with X-Rite)
A prototype tool uses AI to reverse-engineer color profiles from a physical label sample by measuring a few points, allowing converters to accurately reprint jobs without original specifications.
“the software using AI will recalculate, re-engineer, backwards engineer the color profile. Wow. It's just only one of the examples.”
Speaker 2 · Hear it at 15:47
Engineering & simulationEsko prototype (AI tool)
An internal prototype uses AI to analyze design components and materials to generate quotes that include both cost and carbon emission estimates for packaging orders.
“And the software will come up with a quote, not only that, not only dollars in the quote, but also CO emission for that even type of label, that given type of product.”
Speaker 2 · Hear it at 15:47
large enterprises
Other shows on the same ground, closest first.
Peter Gutschi, a consultant supporting companies like ESCATEC and startups, explains how AI is moving beyond hype to drive real efficiency in manufacturing, from shop floor quality management to supply chain planning. He highlights specific technologies such as Luminovo's platform for calculating CO2 footprints and Cybord's component inspection tools, which handle data volumes impossible for humans to manage in real time. Gutschi argues that this enhanced visibility allows EMS providers to accurately commit to delivery dates and prevent the inventory overhangs seen in past crises like the 2000 tech wreck.
Grace O'Malley, Vice President of Technical & Project Operations at iNEMI, explains how the organization transitioned its famous roadmap from a static print document to a dynamic, real-time online platform to better serve the electronics manufacturing industry. She details how the pandemic accelerated collaboration on advanced packaging, smart manufacturing, and sustainability initiatives, including the development of an 'eco-impact estimator' tool. O'Malley highlights the industry's shift from simple material substitution to holistic lifecycle analysis, emphasizing the need for validated data on critical resources and carbon footprints across the entire supply chain.
Kim, CEO of Rapid Robotics, explains how the company pivoted from custom manufacturing automation to end-of-line boxing and palletizing using generative AI to solve labor shortages and handle high SKU variability. She details the development of Rapid ID, which allows robots to identify and handle diverse objects without extensive programming, contrasting this with the limitations of traditional robotics in brownfield environments. Kim also shares her background in the toy industry at Hasbro and how that experience informs her approach to scaling the company and supporting US manufacturing reshoring.
Joel Scutchfield, General Manager of Koh Young America, discusses how economic headwinds and tariff uncertainties are creating a divide in the electronics manufacturing industry, with some companies pausing investment while others expand capacity. He explains that the post-pandemic growth surge was an anomaly, establishing a 'new normal' where manufacturers must leverage AI to increase productivity without expanding their workforce. Scutchfield details Koh Young's progression from data collection to 'agentic' AI systems, specifically highlighting their KAP (Koh Young Auto-Programming) tool and KPO (Koh Young Process Optimization) tools that automate parameter adjustments for printers and mounters. The conversation emphasizes that trustworthy, high-volume 3D data is the critical foundation for these autonomous, self-correcting systems that reduce human intervention on the factory floor.
Priyansha Bagaria, founder and CEO of Loopr.ai, explains how her company uses AI-powered computer vision to automate quality inspection in aerospace, automotive, and general manufacturing. She details the deployment of their software applications, IQ Inspect for defect identification and IQ Verify for assembly verification, which are hardware-agnostic and integrate with existing camera infrastructure. Bagaria highlights key industry pain points, including the high cost of quality, labor shortages, and the loss of institutional knowledge as experienced workers retire, arguing that AI provides the consistency and scalability that human inspection cannot. She also discusses Loopr's strategic partnership with Microsoft and the importance of starting with high-value pilot projects to demonstrate clear ROI before scaling across factory floors.
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