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

Project description

Bridging gaps to safeguard process industries

In the ever-evolving realm of process industries, the pressing challenge of ensuring safety and sustainability looms large. Current methodologies often fall short in addressing the complexity of risk assessment and process safety, leaving a critical gap in industry practices. With the support of the Marie Skłodowska-Curie Actions programme, the PROSAFE project will develop a doctoral training programme to bridge these gaps. It will harmonise robust risk assessment methods and integrate cutting-edge AI and machine learning models to revolutionise the landscape of process safety in industries. The project’s overall aim is to shape a new era in process safety, fostering skilled professionals and addressing vital societal, economic and environmental concerns.

Objective

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.

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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Call for proposal

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(opens in new window) HORIZON-MSCA-2022-DN-01

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Coordinator

DANMARKS TEKNISKE UNIVERSITET
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 905 364,00
Address
ANKER ENGELUNDS VEJ 101
2800 Kongens Lyngby
Denmark

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Region
Danmark Hovedstaden Københavns omegn
Activity type
Higher or Secondary Education Establishments
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Total cost

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