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Design support for the systematic integration of risk reduction into early chemical process design
Institution:1. Delft University of Technology, Safety Science Group, Faculty of Technology, Policy and Management, P.O. Box 5015, 2600 GA Delft, Netherlands;2. Delft University of Technology, Chemical Risk Management Group, Faculty of Applied Sciences Julianalaan 136, 2628 BL Delft, The Netherlands;1. Centre of Technology and Systems, CTS, UNINOVA, 2829-516 Caparica, Portugal;2. Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal;1. Institute of Control and Informatization of Production Processes, Faculty BERG, Technical University of Košice, B. Nemcovej 3, 042 00 Košice, Slovak Republic;2. Department of Furnaces and Thermal Technology, Faculty of Metallurgy, Technical University of Košice, Letná 9, 042 00 Košice, Slovak Republic;1. Division of Life Sciences, Rutgers University, 604 Allison Road, Piscataway, NJ 08854-8082, USA;2. Environmental and Occupational Health Sciences Institute and Consortium for Risk Evaluation with Stakeholder Participation (CRESP), Rutgers University, 604 Allison Road, Piscataway, NJ 08854-88082, USA
Abstract:Design for safety in the chemical industry is becoming a more explicit and well-organised process. However, it requires additional support tools to enable designers to pay attention to safety from the earliest conceptual design stage and through the subsequent detailing and to design more cost-effectively. This paper presents a more explicit approach called design for safety (DfS), which links with approaches already in use, such as layers of protection approach (LOPA). The method consists of two elements, a technology management environment (TME) aimed at supporting the interaction between the many contributors to safe design and a safety modelling language (SML). This provides a rigorous object-oriented language for conceptualising the requirements for risk control (barriers) and analysing their vulnerability to degradation or attack by other system elements or conditions. The method provides a focus for organising and applying existing knowledge about risk control and systematically learning from new knowledge to be gathered and supplied in supporting databases.
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