Looking for consortium for HORIZON-CL4-INDUSTRY-2025-01-TWIN-TRANSITION-01

Turkcell, as one of major mobile phone vendor in Türkiye, aims to reduce e-waste and increase the reuse rate of electronic devices by developing a strategy for collecting, refurbishing, and reselling the phones it sells.

The proposed solution to this problem involves the implementation of state-of-the-art technologies and methodologies. The process will begin with the collection of phones, traceability, and the creation of a digital product passport. The digital product passport will be used to ensure traceability throughout the entire lifecycle of the phones, enhancing transparency during reuse, refurbishment, and recycling processes. Blockchain technology will be employed to maintain secure and immutable records for the digital product passport, thus reducing risks of counterfeiting. IoT-based monitoring sensors will facilitate real-time tracking of collected phones during storage and processing, thereby increasing operational efficiency.

Visual and functional inspection of phones will be conducted using AI-based image processing technologies. Deep learning algorithms will automatically detect and categorize physical damages on the devices. For functional testing, robotic systems will be employed to automate the testing of critical functionalities such as touch screen responsiveness, camera quality, battery health, connectivity features, and processor performance.

During robotic disassembly and reassembly processes, advanced robotic systems will be utilized to ensure rapid and precise handling of the devices. This approach will minimize errors and speed up refurbishment cycles. AI-driven decision-making mechanisms will also be implemented to automatically identify and classify usable components during the refurbishment process.

Machine learning algorithms will be employed to analyze data collected from the refurbished phones, predicting the remaining lifespan of each device and determining the optimal warranty period after refurbishment. For phones that are not suitable for refurbishment, AI-based optimization algorithms will be used to identify reusable parts, ensuring their use as spare components in other devices, thereby minimizing e-waste.