F092: Connected Shop Intelligence: From Digital Twins to Actionable

In their attempts to improve on-time delivery (OTD) and throughput, most manufacturers struggle with traditional scheduling and spreadsheets. The purpose of this presentation is to educate the audience on how to create a Digital Twin of their production environment which then can be used to show future load vs capacity, identify future bottlenecks, determine when any order will finish, quantify personnel requirements, highlight material shortages, and more. We will also explore how the resulting Digital Twin can be used to perform "What-if's" (e.g., add/subtract capacity - people, machines, shifts; add load such as new quotes or possible orders, change priorities), and the resulting impact on OTD and/or Revenue/Contribution Margin (bottom-line impact).

For many discrete manufacturers, the promise of Artificial Intelligence remains just that—a promise. While the industry is rushing to adopt AI tools, most find that their initiatives are crippled by a fundamental "data paradox": AI is only as capable as the data architecture it sits upon. To move from experimental "pilot projects" to measurable ROI, manufacturers must move beyond fragmented modules and embrace a foundation of Connected Manufacturing Data.
This session explores a modern, data-centric framework designed to unify the three disparate layers of a manufacturing enterprise: Interactions (the unstructured relationship data in calls and emails), Transactions (the structured operational data in orders and jobs), and Signals (the real-time streaming data from the shop floor). By connecting these layers, manufacturers can move beyond traditional "isolated modules" to create a live, end-to-end picture of their business.

Key Executive Takeaways:
•The Three Pillars of Intelligence: How to integrate human communication, operational records, and machine telemetry to eliminate the "blind spots" that hinder decision-making.
•The Intelligence Maturity Curve: A roadmap for progressing from Awareness (what is happening?) to Assistance (what should we do?) to Autonomous Execution (let the system handle it).
•Beyond the Chatbot: Why the future of manufacturing relies on specialized AI agents—role-based experts designed to remove specific bottlenecks in finance, compliance, workforce onboarding, and shop floor scheduling.
•Strategic Business Outcomes: How a connected data strategy translates into four critical executive goals:

◦Focus: Moving from "firefighting" to high-impact strategic leadership.
◦Value: Squeezing maximum margin from existing physical and digital assets.
◦Growth: Creating a scalable infrastructure that supports massive revenue expansion without proportional overhead.
◦Potential: Unlocking the hidden capacity in your products, IP, and talent.
By shifting the conversation from "adopting AI" to "connecting data," manufacturing leaders can finally build an enterprise that is not just automated, but truly intelligent.