IRIS Technology Solutions S.L. (IRIS) - Spain

IRIS Technology Solutions S.L. is part of IRIS Technology Group (http://www.iristechnologygroup.com/) is an advanced engineering Group that was established in Barcelona in 2007. It specialises in the manufacture and integration of Process Analytical Technology (PAT)-based real-time quality monitoring
solutions for the process industries and IoT systems for smart manufacturing, predominantly targeted at the food, pharmaceutical and chemical industries. In particular, our product line comprises proprietary state-of-the-art IR analysers for at-line and in-line process monitoring.
On the one hand, our solutions are based on the latest developments in photonics in the fields of MEMs, Near Infrared Spectroscopy, Hyperspectral Imaging, and Raman. On the other hand, we leverage ICTs, whereby we apply Machine learning, Artificial Intelligence and Data Mining techniques for predictive and active control, as well as for decision support systems. In addition to photonics-based analysers, we also work with IoT sensors for enabling equipment and machinery for smart manufacturing and transitioning industry to the Industry4.0 paradigm. Our solutions are cloud-based for mobility, remote monitoring and multi-site applications.
Our Innovation Division which is governed by an Innovation Committee comprising Senior Management, and an Innovation Unit for managing and executing the companies innovation roadmap, has 3 core strategic lines, for shaping the
Factory of the Future:
1. New optical photonics-based technologies and PAT systems for production process optimisation
2. ICTs (Artificial intelligence / machine learning, IOT & cloud platforms)
3. Circular and Bio-based Economy: digitalization and waste valorization
In addition to running an internal R&D programme, as well as carrying our various joint private projects with industry partners, our Innovation Division is highly experienced in working in collaborative R&D projects in H2020 (both as coordinators and partners), principally in the SPIRE, FoF, and BBI programmes. The company was established in 2007 and
currently employs 60+ staff with a turnover of Ä 5 M. It is equipped with engineering workshops (3), food testing and wet chemistry laboratory, optics labs (2), and an electronics/telecommunications lab. IRIS is ISO 9001:2008 certified and also is certified under UNE-EN-ISO 166002: Management Systems R&D&i. We are also certified by the local (Catalonian) government as a provider of technological R&D services (Tecnio Certification). IRIS is a member of the following sectorial networks: SPIRE, SPIE and SECPHO, in addition to regional industrial collectives such as Smart Space (association of companies and organisations that specialise in the ‘smartification’ of industry).
IRIS has a matrix of multidisciplinary knowledge groups in the company with strong expertise in engineering and science. With its team and resources, including electronics, mechatronics, mechanical, optical, industrial design engineers, as well as specialists in system engineering, application programming and web development etc. the group can carry out full system design and engineering, including electronic design and assembly, firmware and software development, electrical harnesses and interconnections, mechanical design for enclosure and prototype integration, as well as installation, validation and industrialisation of prototypes and equipment in production plants. As such they have recently delivered advanced plastic sorting devices. In addition to this broad cross-disciplinary engineering team, IRIS’ research team consists of data scientists, chemiometricians, chemists and physicists, among others, who have the expertise to validate the technologies developed.

Main Task

IRIS will support WP1 where they will test different photonic-based systems for the end of life material identification to ensure they can appropriately be handled with the new process but also in WP4 for the monitoring of the disintegration under the different tested conditions and the development of predictive models that can support the optimisation and upscaling of the new biodegradation approach. Finally they will contribute to the project dissemination and plan an outmost exploitation of their results.

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