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Code Agents: AI-powered end-to-end solutions for flexible manufacturing

Reference number
Coordinator Chalmers Tekniska Högskola AB - Chalmers Tekniska Högskola Inst f Industri- & materialvetensk
Funding from Vinnova SEK 2 000 000
Project duration November 2024 - November 2025
Status Ongoing
Venture Advanced digitalization - Enabling technologies
Call Advanced and innovative digitalization 2024 - one-year projects

Purpose and goal

"Code Agents: AI-Driven End-to-End Solutions for Flexible Manufacturing" enhances production systems through the integration of AI and automation, with a focus on robots and PLCs. By utilizing AI, manufacturers can achieve higher productivity, lower costs, & improved quality. The project develops GenAI-based code generation and validation agents, which enhance adaptive manufacturing processes. Partners involved in the project are Accenture, Chalmers, PTC, Rockwell Automation, and Volvo Cars.

Expected effects and result

Expected project outcomes include: - Verification and validation agents leveraging natural language descriptions, existing code libraries, and sensor data to test robot and PLC code by AI and human programmers. - Digital twin-based verification methods with feedback loops to enhance AI models. - Guidelines for AI-based adaptive code generation to capture business value and scenarios for creating business cases for GenAI services.

Planned approach and implementation

Chalmers is project coordinator. Accenture is assisting with data collection & integration into Gen AI models. PTC provides software & helps set up the database and connection to physical platforms. Chalmers is developing Gen AI-based verification and validation agents in SII-Lab, based on a Volvo Cars case. Rockwell´s Emulate 3D platofrom is used for testing verification and validation agents. Chalmers also investigates how to create business value through such projects and demonstate results.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 19 November 2024

Reference number 2024-03234