If you are a vehicle manufacturer dealing with the fact that 60% to 70% of production resources are scrapped prematurely — this project developed an AI-matchmaking engine and digital twins that allow you to deploy second-hand production lines 40% faster.
AI-Powered Marketplace and Tools for Reusing Industrial Robots and Production Lines
Imagine if factories could trade used robotic arms like we trade used cars, instead of throwing them away while they still work. This system uses a digital matchmaking tool to find the right second-hand equipment for a new factory layout. It's like a smart 'plug-and-play' kit that lets old machinery work perfectly in a new environment.
What needed solving
Manufacturing assets like robotic arms are often scrapped while still functional, leading to massive waste and high replacement costs. This creates a dependency on global supply chains and ignores the value of existing hardware.
What was built
An AI-matchmaking engine for second-hand assets, a machine-readable ontology for requirements, Plug & Produce middleware, and Digital Twin/Shadow APIs.
Who needs this
Who can put this to work
If you are a warehouse automation provider dealing with high equipment costs — this project developed a Circular Manufacturing Ecosystem that can reduce material consumption by up to 80% through asset reuse.
If you are a contract manufacturer dealing with supply chain disruptions — this project developed Plug & Produce middleware that enables the reuse of up to 100% of assets, increasing resilience against global shortages.
Quick answers
How does this affect the cost of setting up a production line?
Based on available project data, the system aims to reduce material consumption by up to 80% and speed up the deployment of second-hand lines by 40%, which significantly lowers capital expenditure.
Can this be scaled to a full industrial plant?
Yes, the project is demonstrating these tools in two real industrial environments at Continental and Comau to prove industrial-scale viability.
What is the IP or licensing model for the AI engine?
Based on available project data, the project is evaluating 'Circularity-as-a-Service' business models for purchasing and operating equipment.
How does it integrate with existing factory hardware?
It uses Plug & Produce middleware and Asset Administration Shells (AAS) to seamlessly connect production assets to the digital ecosystem.
What is the timeline for implementing these tools?
The project runs from 2023 to 2025, with the vision that these resources will be traded across Europe within five to ten years.
Who built it
The consortium is heavily industry-driven with a 62% industry ratio, comprising 8 industrial partners and 3 SMEs. This strong commercial presence, combined with 4 universities across 8 European countries, indicates a high focus on practical application and market adoption rather than pure academic research.
Contact the Technical University of Munich (TUM) regarding the Circular Manufacturing Ecosystem
Talk to the team behind this work.
Contact us to connect with the ALICIA consortium for pilot integration.