Meet the Partner: AIMEN

The Company

AIMEN is a non-profit private association and RTD centre founded in 1967 that specialises in research and technology services related to advanced solutions for industry, the environment, and societal challenges. AIMEN is at the forefront of utilising cutting-edge technologies, which include advanced manufacturing processes incorporating state-of-the-art materials, artificial intelligence, robotics, control systems, and environmental technologies.

It incorporates 73 companies and supplies technological support to more than 500 companies dedicated to industrial or commercial activity linked to metallurgy, the automotive sector, civil construction, or the environment. AIMEN, as a renowned Spanish RTD centre institution situated in Galicia, has made a significant impact on society through its active involvement in a staggering 250 R&D&I projects over the course of the last ten years. This remarkable feat showcases its unwavering commitment to advancing innovation and driving progress. Furthermore, their dedication to pushing boundaries is evident in their portfolio of three patents, which generated an annual income of 17,9 million euros in 2022 while standing as a testament to their pioneering spirit. ​

THE ROLE OF AIMEN INSIDE TRINEFLEX PROJECT

AIMEN is responsible for overseeing project coordination and technical duties associated with digital validation. The objective of this validation is to enhance technology configuration through the utilisation of mathematical models and digital transformation. As part of this, AIMEN is managing and supervising the technical implementation of the ESAMUR demo site. This entails conducting a digital retrofit project that incorporates the deployment of a data acquisition system for monitoring aeration, asset condition, and dynamic energy usage.

Furthermore, AIMEN is currently engaged in the process of incorporating pre-existing sensors into the air pumping system in order to generate data sequences for digital technologies. The objective is to utilise this data for the anticipation and control of operational risks. It additionally leads the digital twin of the aeration process, which incorporates an advanced smart microbial electrochemical sensor for accurate oxygen demand prediction.

Finally, AIMEN has the exciting opportunity to develop a comprehensive lesson-learned outcome from the diverse technological implementations across the 5 demonstration sites. This remarkable experience is set to revolutionise the exchange of information across TRINEFLEX demo cases, creating endless possibilities for replication.

THE benefits Trineflex CAN bring to industries and the environment

TRINEFLEX will serve as a comprehensive solution for Energy Intensity Industries (EIIs) end-users, overseeing the digital lifecycle of the plant and facilitating the transition towards a flexible and sustainable operational framework. This process will be facilitated through the utilisation of cutting-edge and environmentally friendly data acquisition techniques, the implementation of robust Big Data Infrastructures, the meticulous analysis of processes, the development of sophisticated models, and ultimately, the integration of Digital Twins with advanced multi-agent decision support systems. The utilisation of digital data and analytics holds immense potential for enhancing energy and material flexibility, while simultaneously diminishing operational and maintenance costs. This empowers the implementation of predictive maintenance strategies, resulting in cost reductions. In the timeframe leading up to 2040, the implementation of digitalization techniques can result in decreasing operation and maintenance (O&M) costs, which has the potential to yield substantial benefits for companies and, consequently, consumers.

TRINEFLEX partners have a great chance to unlock even greater efficiencies by enhancing industry planning strategies, optimising processes, and minimising loss rates. They also have the chance to overcome obstacles that may arise when implementing novel technologies between TRL 5 and 7. Although it requires a challenging data acquisition infrastructure that needs to cater to the heterogeneity of conditions in each plant and sector, this presents an exciting opportunity for growth and improvement.

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