If you are a recycling yard operator dealing with high worker fatality rates and toxic leaks — this project developed AI drones and magnetic robots that remove humans from hazardous zones. This reduces the risk of work-related diseases and environmental contamination.
AI and Robotics for Safe and Automated Ship Recycling and Material Recovery
Imagine cleaning out a giant, rusty metal maze filled with invisible toxic gases. Instead of sending people in with heavy suits, this project uses a smart drone to map the area and find hazards. Then, magnetic robots crawl along the walls to strip paint and cut the metal, all guided by a digital 3D map of the ship.
What needed solving
Ship recycling is one of the world's most dangerous jobs due to toxic substances and high fatality rates. Current manual processes for hazardous material identification and cutting are slow and risk environmental contamination.
What was built
An AI-powered inspection drone, a digital twin-based automated cutting planner, and two mobile robots (one magnetic for hulls, one manipulator for interiors).
Who needs this
Who can put this to work
If you are a fleet manager dealing with the complex decommissioning of old vessels — this project developed a digital twin and AI planning system. It creates an automated cutting plan to maximize material recovery and ensure regulatory compliance.
If you are a robotics firm dealing with the challenge of operating in GPS-denied, cluttered metal environments — this project developed a mobile manipulator and magnetic track robot. These systems can be adapted for other heavy industrial demolition tasks.
Quick answers
What is the cost or price of implementing these robotic systems?
Based on available project data, specific pricing for the robotic systems is not provided; however, the project is supported by an EU contribution of EUR 7,954,760.
Can this be scaled to industrial-sized ships?
Yes, the project specifically targets the ship recycling industry and uses digital twins of ships to generate automated cutting plans for large-scale disassembly.
How is the IP and licensing handled for the AI algorithms?
Based on available project data, the specific licensing terms are not listed, but the project involves 16 partners including 7 industry players who are developing the AI-based planning methods.
Does this help with environmental regulations?
Yes, it is designed to align with the European Circular Economy Action Plan and Green Deal, specifically targeting the prevention of hazardous material contamination.
How long does it take to integrate the digital twin into the workflow?
Based on available project data, the project period runs from 2024-01-01 to 2027-12-31, indicating a multi-year development and integration timeline.
Who built it
The consortium is heavily industry-weighted with 44% industry participation (7 companies), including 3 SMEs. This strong industrial presence, combined with 6 universities and 2 research centers across 10 countries, suggests a high focus on practical application and commercial viability rather than pure academic research.
Contact HIDROPAR HAREKET KONTROL TEKNOLOJILERI MERKEZI SANAYI VE TICARET ANONIM SIRKETI in Turkey
Talk to the team behind this work.
Contact us to connect with the SHEREC consortium for early adoption of ship recycling robotics.