To boost the shift toward circular manufacturing, CIRCULOOS Open Call 3.1 supports single entities in extending existing pilot value chains by enhancing or adding new R-strategies.
The winning project, RePlastAuto, improves plastic waste management in automotive manufacturing by integrating hyperspectral imaging and machine learning into ELVEZ’s production line. This enables real-time sorting of heterogeneous plastic waste into high-purity, mono-material streams, ready for internal reuse or high-quality recycling—replacing linear waste treatment with a smart, circular approach.
1. Can you briefly introduce your team?
Our team at ELVEZ brings together over 30 years of expertise in injection molding, material science, automation, and sustainable manufacturing. Based in Slovenia, we are a trusted supplier to leading global brands in the automotive and industrial sectors.
The project team from ELVEZ has strong expertise in manufacturing, material science, and automation. Doc. Dr. Dr. Žiga Gosar, Director of R&D and Technology, has a Ph.D. in Non-linear Mechanics and 14 years of experience in strategic R&D, lean manufacturing, and automotive standards. He will lead project strategy and technology integration.
Development Engineers Dr. Luca Petan and Marina Panoska have four years of experience in material science, process optimization, and AI-driven machine vision, focusing on the vision-based sorting system and automation.
Stanislav Remškar, with over 30 years in plastic injection molding, specializes in polymer processing and color matching, leading material selection and process optimization.
Jure Grablovec, Head of Production, oversees manufacturing efficiency, quality control, and compliance.
Jasmina Šakonjić, working in ELVEZ as production technologist, dealing with process optimization and introducing LEAN manufacturing activities.
The Quality Department manages product validation, risk management, and quality assurance. Together, this skilled, multidisciplinary team equips ELVEZ to deliver on all aspects of the CIRCULOOS project, from R&D and automation to production and quality management.
2. What’s your story and what drives you?
What drives us is a commitment to innovation and circularity. We have seen firsthand how traditional linear manufacturing creates high-value products but also generates significant amounts of waste. This challenge inspired us to reimagine our processes and to actively contribute to the circular economy by integrating advanced technologies like AI-powered vision systems, hyperspectral imaging, and digital traceability tools.
Our story is one of evolution and responsibility – from a reliable component manufacturer to an innovation-driven enabler of sustainable value chains. The CIRCULOOS project is a key milestone on this journey, allowing us to demonstrate how digital tools and smart recycling practices can close material loops, reduce environmental impact, and strengthen European manufacturing competitiveness.
3. In simple words, what is your project about and how is it linked with CIRCULOOS?
Our project focuses on turning plastic waste from injection molding into a valuable resource instead of a problem. Normally, leftover or defective plastic parts are mixed together and hard to recycle. With our system, an AI-powered camera sorts the scrap by type and color directly on the production line.
The sorted plastics can then be reused in our own factory for simpler parts or sent to certified recyclers to make high-quality recycled material for the automotive industry. Each batch will be given a digital passport that records what it is made of, its quality, and its carbon footprint. This information will be shared across the supply chain, ensuring traceability and compliance.
This approach closes the loop: plastics flow back into production instead of being wasted. It reduces manual sorting, cuts energy use, and provides data to improve future part designs. In this way, our project directly supports CIRCULOOS’ mission to create digital, connected, and circular value chains across industries.
4. How did you come up with this project idea/concept and what innovative benefits will it bring to the end users?
We developed this project from a clear challenge: manual sorting of plastic waste is slow, error-prone, and cannot deliver the purity needed for high-quality recycling, especially in sectors with strict standards like automotive. To close this gap, we designed a solution that combines AI, robotics, and hyperspectral imaging to automatically identify and sort plastics by type and color directly at the source of waste generation.
The innovation lies in real-time, in-factory sorting combined with digital traceability. This creates cleaner and more consistent recycled materials, reduces contamination, and ensures they meet industry requirements. End users benefit from higher-quality recycled plastics, lower labor costs, and more efficient recycling processes that can be scaled across different waste streams and industries.
In addition, the system generates data on material composition, contamination, and carbon footprint, enabling better supply chain optimization, sustainability reporting, and compliance. This way, industries can increase recycling rates without adding complexity or cost, while moving closer to circular production models.
5. What type of synergies do you want to explore/are already exploring with other circular economy partners?
We are actively building synergies with partners across the circular economy ecosystem, especially in plastic recycling, materials recovery, manufacturing, and sustainability analytics. Our automated sorting system can only achieve full impact when integrated into a wider value chain, so we seek close collaboration with recyclers, plastic processors, and material suppliers. By working with these partners, we ensure that sorted fractions meet input quality requirements, enabling a seamless flow from waste collection to high-value recycled outputs.
We also see strong opportunities in partnerships with data and sustainability platforms. Integrating our system’s data on composition, contamination, and carbon footprint will help improve material traceability and allow partners to strengthen sustainability reporting, optimize supply chains, and meet regulatory demands. Co-development of standards with research institutions and industry bodies is another priority, as it supports harmonization of quality, protocols, and best practices for automated waste sorting and circular product design.
Beyond sorting and recycling, we are exploring synergies in material recovery and feedstock exchange, where one company’s waste can serve as another’s raw material. This creates additional value streams while reducing virgin resource extraction. We also see potential in linking with partners in repair, refurbishing, and remanufacturing, extending product lifecycles and embedding circular principles more deeply across industries.
Through these synergies, we aim to create not only a technical solution but also a collaborative ecosystem that supports industrial-scale circularity, reduces environmental impact, and opens new business opportunities for all stakeholders.
6. What are your plans for the future when it comes to the development of your ideas & projects?
Looking ahead, we plan to further advance the intelligence and adaptability of our automated waste sorting system. Our focus will be on refining machine learning algorithms to detect a broader range of polymers, including dark and multilayer plastics, while enhancing real-time decision-making during sorting.
We also aim to design modular solutions that can be easily integrated into existing material recovery plants or tailored to sector-specific waste streams such as automotive, packaging, and consumer electronics. At the same time, future developments will prioritize reducing energy consumption, increasing system uptime, and minimizing the environmental footprint, ensuring both greater efficiency and sustainability.