Supporting European Industry Success Maximization through Empowerment Centred development

SEISMEC pioneers a transformative approach to digital and industrial technology development, focusing on empowerment, human-centricity, and ethical principles. Through 17 pilot projects across 19 companies in 14 countries and diverse industrial sectors, SEISMEC aims to drive a paradigm shift. The project aims to demonstrate the concept of human-centricity in diverse industry sectors and contexts. Its objectives include empowering skilled workforces, addressing challenges related to advanced workplace technologies, and fostering innovation through evidence-based recommendations. SEISMEC stands as a landmark effort in reshaping European industry toward empowerment and human-centricity, with a strong emphasis on worker security and satisfaction The project evaluates the benefits of human-centricity across various dimensions such as creativity, collaboration, autonomy, and productivity, using CAPS empowerment factors introducing technical innovations like explainability, co-development, and feedback methods to enhance human-centric approaches. It incorporates input from companies and workers, steering them towards an empowered Industry 5.0 path. The consortium comprises leading institutions in engineering, computer science, and networking, coordinated by a world-leading university specializing in social sciences and humanities. SEISMEC’s pilots represent a broad spectrum of sectors, company sizes, and worker roles, ensuring widespread relevance and applicability.

M4D’s role is to oversee a key work package (WP2) about creating methods, guidelines, and tools to improve digital and industrial technologies through human-centered and ethical design. M4D is leading the task for developing Explainable AI (XAI) methods to enhance trust, understanding, and acceptance between people and technology. This includes applying techniques to enhance transparency and trust in machine learning and predictive analytics, making the AI decision-making process understandable and actionable for non-expert users.

M4D is also leading the task to develop algorithms to capture and predict employee feedback to competitiveness while ensuring privacy. This involves refining deep learning algorithms to analyze human behavior through sensors, with a focus on voluntary data collection and privacy protection using edge computing and differential privacy.

Additionally, M4D contributes to designing human-centric interfaces and supports the technical implementation of various pilots within WP3. These include anomaly detection, quality control using machine vision, pattern recognition, and forecasting in time-series data. By leveraging its expertise and resources, M4D contributes to the success of the project and helps drive the adoption of human-centric technologies across European industries.