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.

A collection of theoretical and practical contributions to the modelling of business processes as the key to success for todays companies and organisations. The book thus serves to exchange new ideas in the field while, at the same time, identifying as yet unsolved problems and proffering possible solutions.

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.

This practical book describes the key operations of ARIS Toolset - the market leading Business Process Modelling Tool. Based on his experience of using ARIS in British Telecommunications plc, the author describes practical ways of using the tool. Using screen shots and plenty of practical examples, Rob Davis shows how ARIS can be used to model business processes. Throughout the book Davis provides readers with tips and short-cuts, enabling users to start modelling quickly and effectively. He also provides insights into the ARIS concepts, and tells readers about the benefits and trade-offs of using the tool in alternative ways. Unlike other books, this practical guide tackles issues found in real projects.

Business Process Modeling, Simulation and Design, Third Edition provides students with a comprehensive coverage of a range of analytical tools used to model, analyze, understand, and ultimately design business processes. The new edition of this very successful textbook includes a wide range of approaches such as graphical flowcharting tools, cycle time and capacity analyses, queuing models, discrete-event simulation, simulation-optimization, and data mining for process analytics. While most textbooks on business process management either focus on the intricacies of computer simulation or managerial aspects of business processes, this textbook does both. It presents the tools to design business processes and management techniques on operating them efficiently. The book focuses on the use of discrete event simulation as the main tool for analyzing, modeling, and designing effective business processes. The integration of graphic user-friendly simulation software enables a systematic approach to create optimal designs.

The purpose of this book is to convey to undergraduate students an understanding of those areas of process control that all chemical engineers need to know. The presentation is concise, readable and restricted to only essential elements. The methods presented have been successfully applied in industry to solve real problems. Analysis of closedloop dynamics in the time, Laplace, frequency and sample-data domains are covered. Designing simple regulatory control systems for multivariable processes is discussed. The practical aspects of process control are presented sizing control valves, tuning controllers, developing control structures and considering interaction between plant design and control. Practical simple identification methods are covered.

Master process control hands on, through practical examples and MATLAB(R) simulations This is the first complete introduction to process control that fully integrates software tools--enabling professionals and students to master critical techniques hands on, through computer simulations based on the popular MATLAB environment. Process Control: Modeling, Design, and Simulation teaches the field's most important techniques, behaviors, and control problems through practical examples, supplemented by extensive exercises--with detailed derivations, relevant software files, and additional techniques available on a companion Web site. Coverage includes: Fundamentals of process control and instrumentation, including objectives, variables, and block diagrams Methodologies for developing dynamic models of chemical processes Dynamic behavior of linear systems: state space models, transfer function-based models, and more Feedback control; proportional, integral, and derivative (PID) controllers; and closed-loop stability analysis Frequency response analysis techniques for evaluating the robustness of control systems Improving control loop performance: internal model control (IMC), automatic tuning, gain scheduling, and enhancements to improve disturbance rejection Split-range, selective, and override strategies for switching among inputs or outputs Control loop interactions and multivariable controllers An introduction to model predictive control (MPC) Bequette walks step by step through the development of control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. The book also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve several key control problems, ranging from robustness analyses to biochemical reactors, biomedical problems to multivariable control.