Vicomtech recognized at the Future: Fast Forward initiative event for advancing Smart Factory in the automotive sector

The F3 Group held its annual event on February 11 at Espacio Larra in Madrid under the slogan “Future: Fast Forward, accelerating towards electromobility.” During the event, which brought together key players from across the industry, several awards were presented to the most outstanding subprojects of the PERTE VEC programme, with Vicomtech recognized as one of the awarded entities for its technological leadership.

This recognition highlights the work carried out in project PP-108: “Distributed and Explainable AI to accelerate the transition to the Smart Factory in Electric Vehicles.” This initiative is part of the Future: Fast Forward ecosystem and aims to boost the competitiveness and sustainability of the value chain through cutting-edge collaborative solutions.

A key aspect of this recognition lies in the transfer of real value to industry. Within the project consortium, Vicomtech plays a central role by contributing advanced capabilities in predictive analytics and intelligent optimization in industrial environments, through the development of artificial intelligence models focused on demand forecasting and dynamic production planning.

Leading companies have participated in project PP-108, including Gestamp, with whom Vicomtech has closely collaborated.

Technological innovation and tangible results

Project PP-108 addresses complex challenges such as demand forecasting in highly variable contexts and dynamic process planning. To this end, Vicomtech has implemented hybrid techniques that combine time series modeling with Machine Learning and optimization systems based on Reinforcement Learning.

The technical results achieved to date demonstrate the project’s success and justify its recognition:

• Planning accuracy: A high level of predictive accuracy has been achieved, with mean absolute percentage errors (MAPE) below 5% over short horizons, significantly improving reliability in industrial decision-making.
• Anticipation and flexibility: The developed solutions enable better anticipation of demand deviations and increased production flexibility, allowing plants to dynamically adapt to changes in resources and operational constraints.
• Proven robustness: Reinforcement Learning algorithms have been validated with high stability in simulated environments, ensuring their feasibility for deployment in real industrial settings.
• This recognition consolidates Vicomtech as a key player in the digital transformation of the automotive sector, validating a technological foundation designed to evolve towards more autonomous, secure, and resilient manufacturing environments.