{"id":31123,"date":"2026-04-10T09:00:00","date_gmt":"2026-04-10T09:00:00","guid":{"rendered":"https:\/\/cit.upc.edu\/portfolio-item\/biocholesteroid-nous-materials-intelligents-bio-basats-amb-resposta-optica-per-a-aplicacions-avancades-2\/"},"modified":"2026-04-14T08:03:17","modified_gmt":"2026-04-14T08:03:17","slug":"casandra-data-flows-in-the-supply-chain-integrating-intelligent-decentralised-control-systems-for-the-manufacture-of-large-size-parts","status":"publish","type":"portfolio","link":"https:\/\/cit.upc.edu\/en\/portfolio-item\/casandra-data-flows-in-the-supply-chain-integrating-intelligent-decentralised-control-systems-for-the-manufacture-of-large-size-parts\/","title":{"rendered":"CASANDRA: Data flows in the supply chain integrating intelligent, decentralised control systems for the manufacture of large-size parts"},"content":{"rendered":"\n

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10\/04\/2026<\/p>
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A research team from the Institut de Rob\u00f2tica i Inform\u00e0tica Industrial (IRI, CSIC-UPC), together with the Centre de Disseny d\\’Equips Industrials (CDEI) of the Universitat Polit\u00e8cnica de Catalunya – BarcelonaTech (UPC), are participating in the national CASANDRA project to develop a digital manufacturing solution that will make it possible to establish a bidirectional data flow for continuous digital integration throughout the supply chain across the product life cycle. This integration will be achieved through digital twins and data-based models that are continuously updated thanks to distributed monitoring and control tools.<\/h4>
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The manufacture of large-size components requires the implementation of global data management, together with a comprehensive control methodology, in which the worker continues to play a relevant role in achieving the desired levels of precision, quality and productivity through modular, connected and flexible digital equipment, such as collaborative robotics, augmented and virtual reality (AR\/VR) and exoskeletons.<\/span><\/p>

In this context, the digital architecture proposed in <\/span>CASANDRA<\/a> will enable the aggregation of product, process and resource (PPR) data throughout its life cycle, with the capacity to facilitate data exchange between the different actors in the supply chain. The aim is to design new manufacturing strategies that are more precise, efficient and sustainable for large-size components.<\/span><\/p>

Progress in the concept of the \u201cconnected factory\u201d will make it possible to develop new data analysis strategies capable of managing the data collected throughout the product life cycle. This opens the door to progress towards the concept of the \u201cautonomous factory\u201d, which will make it possible <\/span>to implement a comprehensive decision-support system and visualisation tools capable of providing recommendations to optimise the different phases of the manufacturing process.<\/span><\/p>

Among the objectives of the CASANDRA project is to provide the large-size component industry with a data structure that makes it possible to have a production process connecting engineering, production and manufacturing. This will be achieved by using hybrid models that combine computational and mathematical models with production and quality data, through human-centred artificial intelligence (AI) models and digital solutions that lead to defect-free production, with continuous monitoring of production quality and improvement of working conditions through monitoring, as well as the use of digital twins, robotic solutions or exoskeletons.<\/span><\/p>

These tools are expected to be implemented in a shipbuilder (NODOSA) and a large-scale boilermaking manufacturer (IDESA).<\/span><\/p>

On the one hand, the IRI will work on:<\/span><\/p>



Monitoring of the worker\u2019s condition: developing operator monitoring methodologies to minimise occupational risks in high-risk tasks, such as welding in confined spaces.<\/span>

Operator ergonomics and development of control algorithms with exoskeletons: analysis of the type of effort made by the operator and implementation of exoskeleton-based solutions that minimise their fatigue, increasing productivity and reducing the risk of injury.<\/span>

Development of robotic learning algorithms: learning, both by demonstration and with digital twins, to control and move a robotic arm for collaborative tasks with human beings, including methodologies that guarantee their safety.<\/span>



On the other hand, the CDEI-UPC\u2019s contribution to the project will consist of:<\/span><\/p>



Development of advanced mathematical models using Computer-Aided Engineering (CAE) tools, integrated with real manufacturing data to improve efficiency and precision in the manufacture of large-scale components.<\/span>

Simulation of processes based on these models, considering material properties and thermal behaviour, and improvement, where appropriate, with real-time sensor data, increasing precision and reducing the need for physical sensors through hybrid models.<\/span>

Optimisation of manufacturing processes through simulations with continuous updates to reflect current conditions: digital twins will simulate processes in a virtual environment, while in-line dimensional control will make it possible to detect and correct defects at an early stage.<\/span>



Consortium, Budget and Funding<\/h4>

The consortium is made up of 13 partners, divided between the CDTI group, comprising DGH (coordinator), ONS, ARSOFT, TRIMEK, NVISION, GOGOA, NODOSA and IDESA; and the AEI group, comprising AIMEN (coordinator), the IRI (CSIC-UPC), the CDEI (UPC), CITIC (UdC) and INNOVALIA.<\/span><\/p>

CASANDRA (code PLEC2024-011174) is a \u2018L\u00edneas estrat\u00e9gicas: TRANSMISIONES 2024\u2019 project and has a total budget of \u20ac6,973,499. The project has a duration of 4 years (January 2025 – December 2028).<\/span><\/p>
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\"CASANDRA\"


\"CASANDRA\"


\"CASANDRA\"

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Digital Transformation<\/a><\/p>
Tecnolog\u00eda
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Industry 4.0<\/a><\/p>
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