F057: The Smart Shop Stack: QR Tools, Data Foundations & Agentic AI for Next-Level Manufacturing

Numerous technologies are promoted as a means to drive efficiency. Few, however, live up to this promise. QR codes are the exception, but only if manufacturers understand where and when to utilize them. Metalphoto of Cincinnati's OEM expert will provide a scalable framework for QR code adoption, making it user-friendly and accessible across departments from maintenance to engineering, to the C-suite.

Upon completing this session, attendees will learn:

< !1.) The benefits of QR codes in manufacturing

< !2.) How to identify gaps in manufacturing processes and where QR code implementation offers the most value

< !3.) Real-world examples highlighting different manufacturers currently using QR codes and the various ways QR codes are deployed in those environments

Your path to streamlined workflows, data-driven operations and precise traceability begins with this educational session.

Manufacturing generates massive amounts of machine data, but much of it is fragmented by equipment brand and system, making it inconsistent and difficult to use within daily operations and enterprise systems. In this session, Rob Longfellow, CTO of Juxtum, will share how manufacturers can securely access data from their shop floor assets and integrate it seamlessly into the platforms they already use. By breaking down silos, standardizing inputs, and building scalable data pipelines, organizations can improve data reliability, reduce manual workarounds, and enable faster, more confident decision making. Attendees will learn why a strong manufacturing data infrastructure directly supports process optimization and production profitability and how this can be implemented today without disruption.

AI in manufacturing often stalls at pilots and dashboards. This session presents a production-ready approach: embedding agentic AI directly into a manufacturing operating system to automate real process workflows.

Using a live case study from StartProto, we demonstrate how a graph-based data model of parts, routings, and historical production data enables AI agents to reason with full operational context—and take action. Applications include automatically generating work plans from CAD drawings, building quotes, creating staggered production jobs from purchase orders, drafting purchase orders from shop-floor images, and proactively monitoring KPIs.

In one example, two to three hours of manual planning work were reduced to under ten minutes. Across deployments, optimized scheduling has driven ~30% efficiency gains.

Attendees will gain a practical framework for implementing AI beyond chat interfaces—covering reasoning, context architecture, execution guardrails, ITAR-compliant deployment, and integration with legacy ERP systems.