IMTS 2026 Conference to Tackle Conversational AI on the Shop Floor

Large Language Models (LLMs) have already reshaped office productivity by connecting AI to enterprise data and documents. At the IMTS 2026 Conference, a new session will examine how that same capability is reaching the manufacturing floor — and what it actually takes to make production equipment conversational.

The session, Making Machines Conversational: Connecting Manufacturing Equipment to AI Chat Agents, is scheduled for Thursday, September 17 at 9:00 A.M. in IMTS52 Room W192-A. It will be presented by Andy Joseph, Vice President of Engineering at Promess Incorporated.

The data is already there

The premise is straightforward: modern CNC machines, assembly systems, and process equipment generate vast amounts of operational data — machine status, process parameters, part-level diagnostics, quality data, and real-time performance metrics. That data is accessible through industrial protocols like OPC UA, MTConnect, fieldbus systems, and HTTP-based APIs, depending on the controller architecture.

What's changed is the tooling. AI tooling frameworks, such as the Model Context Protocol (MCP), now allow chat agents like ChatGPT and Claude to interface directly with manufacturing equipment. By creating custom tools that bridge communication protocols, AI agents can access real-time machine data, historical performance records, and technical documentation — and answer operator questions in natural language.

From press to chat agent

Joseph will demonstrate how to build an AI-ready technical corpus for manufacturing equipment, combining machine-specific documentation, real-time data feeds, operational context, and historical data. The presentation includes lessons learned from a real-world implementation connecting a Promess electromechanical assembly press to Claude AI, followed by a live demonstration of natural language interaction with production equipment.

Accuracy on the shop floor is non-negotiable, and the session addresses that directly.

He'll share optimization strategies to improve response accuracy, minimize AI hallucinations, and increase explainability – critical for shop floor applications.

Attendees will gain practical knowledge for implementing conversational AI on their own manufacturing floor, including architecture considerations, data preparation strategies, and integration approaches that work with existing machine communication standards.

About the presenter

Joseph brings more than 28 years of experience in software, controls, and manufacturing systems to the topic. He holds several U.S. patents in industrial automation and smart manufacturing technologies. His current work focuses on applying machine learning, cloud technologies, and conversational AI to manufacturing equipment — making complex machine data more accessible to engineers and operators. He holds a B.S. from the University of Michigan and an M.S. from Kettering University.