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

Business Process Modeling, Simulation and Design covers the design of business processes from a broad quantitative modeling perspective. The text presents a multitude of analytical tools that can be used to model, analyze, understand and ultimately, to design business processes. The range of topics in this text include graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, as well as the use of Data Envelopment Analysis (DEA) for benchmarking purposes. And a major portion of the book is devoted to simulation modeling using a state of the art discrete-event simulation package.

Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

[Special Note: If you ordered in early September, please contact www.processmodelingadvisor.com to receive your FREE final-edited copy directly from the author.] Many business process models don't meet expectations. Why? Business analysts, managers, productivity improvement specialists, and consultants who develop process models by trial and error are prone to fail. This is THE only start-to-finish how-to guide for consistently producing high-quality business models. It shows you how to: - Establish or improve your business process modeling competence using the 6-step Universal Process Modeling Procedure. - Perceive, define/normalize any business process or activity using the 4-part Universal Business Process Definition. - Never miss the 3 Basic Business Process Flow elements. - Efficiently elicit process model content using razor-sharp elicitation agendas. - Elicit and model the 10 most common logical process model refinements. - Validate any process model's quality using 5 Universal Process Model Quality Checklists. - Use any process modeling tool at-hand, whether it be white board or process modeling software. Learn more at www.ProcessModelingAdvisor.com

This book covers the area of product and process modelling via a case study approach. It addresses a wide range of modelling applications with emphasis on modelling methodology and the subsequent in-depth analysis of mathematical models to gain insight via structural aspects of the models. These approaches are put into the context of life cycle modelling, where multiscale and multiform modelling is increasingly prevalent in the 21st century. The book commences with a discussion of modern product and process modelling theory and practice followed by a series of case studies drawn from a variety of process industries. The book builds on the extensive modelling experience of the authors, who have developed models for both research and industrial purposes. It complements existing books by the authors in the modelling area. Those areas include the traditional petroleum and petrochemical industries to biotechnology applications, food, polymer and human health application areas. The book highlights to important nature of modern product and process modelling in the decision making processes across the life cycle. As such it provides an important resource for students, researchers and industrial practitioners. Ian Cameron is Professor in Chemical Engineering at the University of Queensland with teaching, research, and consulting activities in process systems engineering. He has a particular interest in process modelling, dynamic simulation, and the application of functional systems perspectives to risk management, having extensive industrial experience in these areas. He continues to work closely with industry and government on systems approaches to process and risk management issues. He received his BE from the University of New South Wales (Australia) and his PhD from imperial College London. He is a Fellow of IChemE. Rafiqul Gani is a Professor of Systems Design at the Department of Chemical and Biochemical Engineering, Technical University of Denmark, and the director of the Computer Aided Product-Process Engineering Center (CAPEC). His research interests include the development of computer-aided methods and tools for modelling, property estimation and process-product synthesis and design. He received his BSc from Bangladesh University of Engineering and Technology in 1975, and his MSc in 1976 and PhD in 1980 from Imperial College London. He is the editor-in-chief of Computers and Chemical Engineering journal and Fellow of IChemE as well as AIChE. Product and process modelling; a wide range of case studies are covered Structural analysis of model systems; insights into structure and solvability Analysis of future developments; potential directions and significant research and development problems to be addressed

This book describes in detail how ARIS methods model and identify business processes by means of the UML (Unified Modeling Language), leading to an information model that serves as the basis for a systematic and intelligent development of application systems. Multiple real-world examples using SAP R/3 illustrate aspects of business process modeling including methods of knowledge management, implementation of workflow systems and standard software solutions, and the deployment of ARIS methods.

Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London, this book includes theoretical developments, algorithms, methodologies and tools in process systems engineering and applications from the chemical, energy, molecular, biomedical and other areas. It spans a whole range of length scales seen in manufacturing industries, from molecular and nanoscale phenomena to enterprise-wide optimization and control. As such, this will appeal to a broad readership, since the topic applies not only to all technical processes but also due to the interdisciplinary expertise required to solve the challenge. The ultimate reference work for years to come.

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.

Business processes are among today's hottest topics in the science and practice of information systems. Business processes and workflow management systems attract a lot of attention from R&D professionals in software engineering, information systems, business-oriented computer science, and management sciences. The carefully reviewed chapters contributed to this state-of-the-art survey by internationally leading scientists consolidate work presented at various workshops on the topic organized by the editors of the book in the past few years. The book spans the whole spectrum of business process management ranging from theoretical aspects, conceptual models, and application scenarios to implementation issues. It will become a valuable source of reference and information for R&D professionals active in the fascinating interdisciplinary area of business process management and for ambitious practitioners.

An introduction to the modeling of business information systems, with processes formally modeled using Petri nets. This comprehensive introduction to modeling business-information systems focuses on business processes. It describes and demonstrates the formal modeling of processes in terms of Petri nets, using a well-established theory for capturing and analyzing models with concurrency. The precise semantics of this formal method offers a distinct advantage for modeling processes over the industrial modeling languages found in other books on the subject. Moreover, the simplicity and expressiveness of the Petri nets concept make it an ideal language for explaining foundational concepts and constructing exercises. After an overview of business information systems, the book introduces the modeling of processes in terms of classical Petri nets. This is then extended with data, time, and hierarchy to model all aspects of a process. Finally, the book explores analysis of Petri net models to detect design flaws and errors in the design process. The text, accessible to a broad audience of professionals and students, keeps technicalities to a minimum and offers numerous examples to illustrate the concepts covered. Exercises at different levels of difficulty make the book ideal for independent study or classroom use.