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Smart Integration of Process Systems Engineering & Machine Learning for Improved Process Safety in Process Industries

Description du projet

Combler les lacunes pour préserver les industries de transformation

Dans le domaine en constante évolution des industries de transformation, le défi pressant d’assurer la sécurité et la durabilité se profile à l’horizon. Les méthodologies actuelles sont souvent insuffisantes pour répondre à la complexité de l’évaluation des risques et de la sécurité des processus, ce qui laisse une lacune importante dans les pratiques de l’industrie. Avec le soutien du programme Actions Marie Skłodowska-Curie, le projet PROSAFE développera un programme de formation doctorale pour combler ces lacunes. Il harmonisera des méthodes robustes d’évaluation des risques et intégrera des modèles d’IA et d’apprentissage automatique de pointe pour révolutionner le paysage de la sécurité des procédés dans les industries. L’objectif global du projet est d’ouvrir une nouvelle ère dans le domaine de la sécurité des procédés, en encourageant les professionnels qualifiés et en répondant aux préoccupations sociétales, économiques et environnementales essentielles.

Objectif

PROSAFE proposes a novel doctoral training program in the multidisciplinary field combining machine learning, artificial intelligence, and process systems engineering with domain knowledge of process industry and process safety. PROSAFE will pioneer new foundations by integrating Quantitative Risk Assessment, Process Systems Engineering (PSE) with interpretable machine learning (ML) and artificial intelligence (AI) disciplines as targeted breakthroughs to achieve the objectives. To this end, PROSAFE will develop new synergistic tools and train skilled professionals to address this very important societal, economic, and environmental challenge of safe and sustainable process industries. PROSAFE research objectives are:
1: Harmonize robust QRA methods and implementation strategies for effective and improved risk assessment and process safety
2: Develop AI and ML (interpretable ML) models using domain knowledge for efficient, safe, and reliable operations
3: Develop synergistic integration of model-based with data-based methods for improved process safety operation and monitoring
4: Demonstration and validation of PROSAFE novel concepts and methods on industrial relevant case studies for safer operation
PROSAFE's major training objectives are:
1: Training of doctoral candidates (DCs) through individual projects combining multidisciplinary competences in the areas of AI, ML, and PSE within the domain of process safety
2: Establish and pilot the concept of a truly interdisciplinary European multicenter training program in AI/ML, QRA, and PSE within the domain of safety in process industries through relevant network-wide events, courses, workshops, and on-site industry training that complements training in soft skills for effective communication and entrepreneurship.
Through this research and training program, PROSAFE will contribute to realizing the promising potential of the new artificial intelligence paradigm with a particular focus on process safety in process industries.

Coordinateur

DANMARKS TEKNISKE UNIVERSITET
Contribution nette de l'UE
€ 905 364,00
Adresse
ANKER ENGELUNDS VEJ 101
2800 Kongens Lyngby
Danemark

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Région
Danmark Hovedstaden Københavns omegn
Type d’activité
Higher or Secondary Education Establishments
Liens
Coût total
Aucune donnée

Participants (4)

Partenaires (5)