Why This Workshop, Why Now

Most MES training teaches the Core Four — OEE, work order management, scheduling, and downtime tracking — as static configuration: click here, configure that, done. That's not how MES gets built anymore, and it's not how this workshop teaches it.

Day 1 opens with an AI agent as co-architect — helping design the UNS namespace, the MES data model, and the integration plan before a single line of configuration exists. In between, you build the real thing: a working, single-line MES on Ignition, PostgreSQL, CoreFlux, and UNS Studio. Day 2 closes with that same AI agent working inside the finished system — answering natural-language questions about OEE and downtime, flagging anomalies, and assisting with work orders and scheduling.

That's the post-agentic MES: a system designed and operated with AI woven through it from the first architecture decision to the last query — not a traditional MES with a chatbot added on top.

Who this course is for

This workshop is built for engineers, integrators, and end-users who already have hands-on familiarity with core MES concepts and the surrounding stack. This is explicitly not an introductory course.

What You Should Already Know

• Ignition
• PostgreSQL
• UNS / MQTT
• LLMs / AI (basic prompting)
• Core MES concepts

What We'll Refresh (Briefly)

Lesson 1 covers the primary MES refresher: what MES is, what it isn't, where it fits, MES vs. ERP/SCADA/UNS, and the core MES functions. Beyond that, we'll weave in light, contextual refreshers on Ignition, PostgreSQL, UNS, and LLMs as each is used.

We are not teaching Ignition fundamentals, SQL fundamentals, MQTT fundamentals, UNS fundamentals, or prompting from scratch — come ready to move fast.

AI at Both Ends of the Build

Front end: AI helps design and integrate the MES.

Middle: You build the Core Four MES functions.

Back end: AI is integrated into the functioning MES — querying, analyzing, and assisting with OEE, downtime, work orders, and scheduling.

Note: Session recordings will be provided to all registrants and posted to iiot.university.

What you'll learn

• Architect a UNS namespace and MES data model with an AI agent as co-designer
• Stand up a live MQTT/UNS backbone (CoreFlux + UNS Studio) and a PostgreSQL data layer for MES
• Build a working OEE calculation and visualization pipeline in Ignition
• Build a full work-order lifecycle — create, dispatch, execute, track, complete
• Build a live scheduling module that sequences and prioritizes work against the line
• Build automatic and operator-reported downtime tracking with reason-code root-cause capture
• Put an AI agent to work inside the finished MES — natural-language queries, anomaly flagging, work-order and scheduling assistance
• Leave with your build, handed off to you through a private GitHub repo

Requirements

• Working familiarity with Ignition, PostgreSQL, UNS/MQTT, and basic LLM/AI prompting (see "What You Should Already Know" above)
• A laptop capable of running the workshop's stack — Ignition, PostgreSQL, and the UNS/MQTT tooling
• GitHub account, with your username submitted to our team before the workshop
• Access to the workshop's AI tooling (Notus) — details on getting set up will be sent ahead of time