Imagine if every product you bought came with a digital diary that tracked its health and location. When it's time to throw it away, the manufacturer knows exactly what's inside and how to fix it without guessing. It's like having a GPS and a medical record for a washing machine or a car part to make recycling effortless.
Manufacturers lose critical data about their products once they are sold, making it nearly impossible to efficiently recover, refurbish, or recycle them. This leads to wasted raw materials and high labor costs during the disassembly process.
An open-access digital platform and a set of integrated tools using AI, IoT, and AR to track product health and optimize the recovery of parts.
If you are a whitegoods manufacturer dealing with inefficient part recovery — this project developed a digital platform that can increase spare part recovery efficiency by 90%, saving 126,000 labour hours for refrigerators.
If you are a remanufacturer dealing with high material waste — this project developed tracking and monitoring tools that can increase the spare part recovery rate by 20%, leading to 6,000 tons of net material savings.
If you are an electronics company dealing with lost data after a product is sold — this project developed an open-access digital platform that tracks product conditions to optimize the return and refurbishing process.
Based on available project data, specific pricing or cost structures for the digital platform are not provided.
Yes, the project demonstrates solutions across three major industrial sectors (whitegoods, electronics, and automotive) that represent over two-thirds of the European Economy.
The project aims to develop an open-access digital platform for lifecycle information management, though specific licensing terms are not detailed in the provided text.
It uses IoT, Big Data, and AI to optimize reverse logistics by providing real-time data on the location and condition of products before they enter the recovery phase.
The project is active from January 1, 2023, to December 31, 2026.
The consortium is heavily industry-driven, with 7 industrial partners (58% of the group) and 3 SMEs, ensuring the solutions are grounded in commercial reality. It spans 8 countries and combines the academic research of 4 universities with 1 dedicated research center, balancing technical AI/IoT development with practical application in the automotive and electronics sectors.
Contact Masarykova univerzita in the Czech Republic
Contact us to explore how to integrate DiCiM's recovery metrics into your supply chain.
