Case Study
Case Study
“The principal researcher can create their own data product in a simple way and use the Granta MI platform to curate the data in a validated manner. This gives us a guarantee that we can reuse the data in the future and constitutes a huge competitive advantage.”
— José Antonio Chica-Páez
Digital Transformation Leader at Energy Transition Business Unit, TECNALIA
As Spain’s largest applied research and technological development center, TECNALIA is central to transforming technological research into public benefit. Serving thousands of public and private sector clients, TECNALIA’s work in materials innovation is critical for driving advancements in energy, construction, manufacturing, and mobility. However, decades of project-based work created a significant challenge: fragmented data stored in isolated silos. This approach hindered the ability to reuse knowledge across projects, led to repetitive testing, and made comprehensive data analysis nearly impossible. To overcome these hurdles and unlock the full value of its vast materials data, TECNALIA required a robust, centralized platform to build a new, more strategic data-driven approach.
Figure 1. “A construction component manufactured using 3D-printed cement mortar”.
Figure 2. "Advanced surface engineering processes to enhance material resistance, protection, and functionality."
Figure 3. "Cross-sectional SEM view of a PVD, Physical Vapor Deposition, coating designed to enhance wear resistance and corrosion protection."
TECNALIA implemented Ansys Granta MI software to power a centralized knowledge base, shifting from simple data repositories to a more ambitious "data products" concept. The platform enabled researchers to create and curate their own data products using familiar tools, which lowered the barrier to adoption and accelerated a cultural shift.
The ability of the Granta MI platform to manage traceability, access control, IP protection, and quality control were critical features for making the data product concept a reality. The solution's interoperability with other business systems and the capability to extract information programmatically with the Python programming language for advanced analysis were key to its success.
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