A New Approach to HAZOP of Complex Chemical Processes provides practical methods to identify and categorize chemical process complexities systematically. The book follows a holistic assessment of risks and required safeguards which enables readers to define the boundaries of HAZOP 4.0 accurately. The book is written by authors who have decades of experience in advanced process monitoring and artificial intelligence to support HAZOP teams with a holistic dynamic simulation and multivariable monitoring of the complex systems, and to assess historical failure and accident data and information using artificial intelligence techniques in a user-friendly way.
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Fabienne-Fariba Salimi has over 30 years of experience as a chemical process engineer. She has experience in Management and Chemical Process Safety engineering in oil and gas industries both offshore and onshore installations. She has particular expertise is dynamic simulation of chemical processes and accident consequence modelling in quantitative risk analysis. Her main qualifications were obtained in Iran and France and she is member of the Institute of Chemical Engineers, American Institute of Chemical Engineers, International Society of Automation, and Association of the French System Engineers. She is the co-developer of ADEPP and has been the Project Manager of ADEPP Academy since 1994.
Ali Akbar Safavi received his B.S. degree in Electrical Engineering from Shahid Chamran University, Iran, in 1987, and his M.Sc. degree in Control Engineering from the University of NSW, Australia, in 1992. His Ph.D. in Process Systems Engineering was completed at Sydney University in 1995. In 1996, he was a Postdoctoral fellow in Sydney University. He joined Shiraz University in 1997. He is currently a Professor in the School of Electrical and Computer Engineering at Shiraz University in Iran. He has been principal investigator of several industrial projects and several international project. He is author of several books and more than 250 papers. For many years, has been the Directing Board Member of various Scientific Associations including ISICE, YADA, etc. His research interests are model predictive control, wavelets, neural networks, system identification, networked based control, and information technology, IIoT, and Industry 4.0. and Industry 5.0. See https://safavi.home.shirazu.ac.ir/,
http://linkedin.com/in/ali-akbar-safavi-90451039.
Leonhard Urbas studied information technology in mechanical engineering in Technische Universität Berlin (1988-1993). He was research associate at the institute of Process and Plant Engineering in TU Berlin from 1993 to 1997. In 1998, he had topic and project responsibility in the field of automation technology at degussa AG, Hanau/Köln/Dortmund from for two years. From 2000 to 2006, he was the leader of junior research group "Bedienermodellierung in dynamischen Mensch-Maschine-Systemen" in TU Berlin. He is currently the head of the Chair of Process Control Systems and the Process Systems Engineering Group at Technische Universität Dresden, Dresden, Germany, and a professor. His research interests include engineering of distributed safety-critical systems, in particular function integration, model-driven engineering and modularization; information models of the process industry, process information and management systems and middleware in automation engineering; usability of multimodal and mobile interfaces in automation systems; Analysis, design and evaluation of alerting and support systems; methods of user modeling for prospective design of human-technology interaction. See:
https://tu-dresden.de/ing/elektrotechnik/ifa/plt/die-professur/mitarbeiter/leon-urbas
Frederic Salimi has over 35 years of experience in safety engineering and petrochemical design in oil and gas industries both onshore and offshore. He has experience in HSE management and risk based design for EPC projects. His expertise includes Safety & Environment code and standard compliance, pipeline risk assessment, critical system identification, and Qualitative and Quantitative Risk Assessment. His main qualifications in Physics and RAMS were obtained in Iran and France. He is a member of the American Institute of Chemical Engineers. He is the co-author of ADEPP and co-founder of the ADEPP Academy.
Effective implementation of Industry 4.0 in process facilities requires the modernization of quality and process safety management systems and their elements to QMS 4.0 and PSM 4.0. In the context of hazard identification and risk assessment element of PSM, HAZOP plays an essential role for the design and operation of the process safeguards against hazardous operating scenarios and predictive maintenance of the safety critical equipment. Therefore HAZOP should be modernized to HAZOP 4.0 too.
A New Approach to HAZOP of Complex Chemical Processes raises awareness that oversimplification of complex processes or hazardous operating scenarios could lead to major accidents. The book proposes practical methods to identify and categorize process complexities systematically and follows a holistic assessment of their risk and required safeguards which enables you to define the boundaries of the HAZOP 4.0 accurately.
The book is written by authors who have decades of experience in advanced process monitoring and artificial intelligence (AI) to (1) support HAZOP teams with a holistic dynamic simulation and multivariable monitoring of the complex systems and (2) access data and information of historical failures and accidents using AI techniques in a user-friendly way.E
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Taschenbuch. Zustand: Neu. Neuware - A New Approach to HAZOP of Complex Chemical Processes provides practical methods to identify and categorize chemical process complexities systematically. The book follows a holistic assessment of risks and required safeguards which enables readers to define the boundaries of HAZOP 4.0 accurately. The book is written by authors who have decades of experience in advanced process monitoring and artificial intelligence to support HAZOP teams with a holistic dynamic simulation and multivariable monitoring of the complex systems, and to assess historical failure and accident data and information using artificial intelligence techniques in a user-friendly way. Artikel-Nr. 9780323905626
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