A unique text covering basic and advanced concepts of optimization theory and methods for process systems engineers. With examples illustrating key concepts and algorithms, and exercises involving theoretical derivations, numerical problems and modeling systems, it is ideal for single-semester, graduate courses in process systems engineering.

Process systems engineering (PSE) is a discipline that delivers tools for guided decision-making in the development of new processes and products. Proven successful in the pharmaceutical-, food- and water sectors, it has also breached the field of energy systems. The future energy systems aim to be more efficient, cost-effective, environmentally benign, and interconnected. The design and operation is extremely challenging for decision-makers, engineers, and scientists and here lies a crucial role for the process systems engineer.

Process Systems Risk Management provides complete coverage of risk management concepts and applications for safe design and operation of industrial and other process facilities. The whole life cycle of the process or product is taken into account, from its conception to decommissioning. The breadth of human factors in risk management is also treated, ranging from personnel and public safety to environmental impact and business interruption. This unique approach to process risk management is firmly grounded in systems engineering. Numerous examples are used to illustrate important concepts –drawn from almost 40 years authors' experience in risk analysis, assessment and management, with applications in both on- and off-shore operations. This book is essential reading on the relevant techniques to tackle risk management activities for small-, medium- and large-scale operations in the process industries. It is aimed at informing a wide audience of industrial risk management practitioners, including plant managers, engineers, health professionals, town planners, and administrators of regulatory agencies. - A computational perspective on the risk management of chemical processes - A multifaceted approach that includes the technical, social, human and management factors - Includes numerous examples and illustrations from real life incidents

Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents. To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises. - Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation - Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling - Illustrates the notions, tools, and techniques of process modeling with examples and advances applications

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering

With growing global competition, the process industries must spare no effort in insuring continuous process improvement in terms of Increasing profitability; Conservation of resources and Prevention of pollution. The question is how can engineers achieve these goals for a given process with numerous units and streams? Until recently conventional approaches to process design and operation put emphasis only on individual units and parts of the process. A more powerful integrated approach was lacking. The new field of Process Integration looks towards the processing plant as a whole in its attempt to find solutions and improvements. Research over the past two decades has resulted in many techniques that allow engineers to better understand complex facilities and significantly enhance their performance. This textbook presents a comprehensive and authoritative treatment of the concepts, tools and applications of Process Integration. Emphasis is given to systematic ways of analyzing process performance. Graphical, algebraic and mathematical procedures are presented in detail. In addition to covering the fundamentals of the subject, the book also includes numerous case studies and examples that illustrate how Process Integration is solving actual industrial problems. - Systematic methodology for analyzing the process as an integrated system, identifying global insights of the process, and generating optimum strategies and solutions - Proper mix of fundamental principles, insightful tools, and industrial applications - Generic techniques that are applicable to a wide variety of processing facilities - Packed with case studies, practical tools, charts, tables, and performance criteria - Extensive bibliography to provide ready access to process integration literature - Excellent review of state-of-the-art technology, development trends, and future research directions

A comprehensive overview of current developments and applications in biofuels production Process Systems Engineering for Biofuels Development brings together the latest and most cutting-edge research on the production of biofuels. As the first book specifically devoted to process systems engineering for the production of biofuels, Process Systems Engineering for Biofuels Development covers theoretical, computational and experimental issues in biofuels process engineering. Written for researchers and postgraduate students working on biomass conversion and sustainable process design, as well as industrial practitioners and engineers involved in process design, modeling and optimization, this book is an indispensable guide to the newest developments in areas including: Enzyme-catalyzed biodiesel production Process analysis of biodiesel production (including kinetic modeling, simulation and optimization) The use of ultrasonification in biodiesel production Thermochemical processes for biomass transformation to biofuels Production of alternative biofuels In addition to the comprehensive overview of the subject of biofuels found in the Introduction of the book, the authors of various chapters have provided extensive discussions of the production and separation of biofuels via novel applications and techniques.