Design of Industrial Information Systems presents a body of knowledge applicable to many aspects of industrial and manufacturing systems. New software systems, such as Enterprise Resource Planning, and new hardware technologies, such as RFID, have made it possible to integrate what were separate IT databases and operations into one system to realize the greatest possible operational efficiencies. This text provides a background in, and an introduction to, the relevant information technologies and shows how they are used to model and implement integrated IT systems. With the growth of courses in information technology offered in industrial engineering and engineering management programs, the authors have written this book to show how such computer-based knowledge systems are designed and used in modern manufacturing and industrial companies. Introduces Data Modeling and Functional Architecture Design, with a focus on integration for overall system design Encompasses hands-on approach, employing many in-chapter exercises and end-of-chapter problem sets with case studies in manufacturing and service industries Shows the reader how Information Systems can be integrated into a wider E-business/Web-Enabled Database business model Offers applications in Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES)

It is 5 years since the publication of the seminal paper on “Design Science in Information Systems Research” by Hevner, March, Park, and Ram in MIS Quarterly and the initiation of the Information Technology and Systems department of the Communications of AIS. These events in 2004 are markers in the move of design science to the forefront of information systems research. A suf cient interval has elapsed since then to allow assessment of from where the eld has come and where it should go. Design science research and behavioral science research started as dual tracks when IS was a young eld. By the 1990s, the in ux of behavioral scientists started to dominate the number of design scientists and the eld moved in that direction. By the early 2000s, design people were having dif culty publishing in mainline IS journals and in being tenured in many universities. Yes, an annual Workshop on Information Technology and Systems (WITS) was established in 1991 in conju- tion with the International Conference on Information Systems (ICIS) and grew each year. But that was the extent of design science recognition. Fortunately, a revival is underway. By 2009, when this foreword was written, the fourth DESRIST c- ference has been held and plans are afoot for the 2010 meeting. Design scientists regained respect and recognition in many venues where they previously had little.

This book provides guidelines for practicing design science in the fields of information systems and software engineering research. A design process usually iterates over two activities: first designing an artifact that improves something for stakeholders and subsequently empirically investigating the performance of that artifact in its context. This “validation in context” is a key feature of the book - since an artifact is designed for a context, it should also be validated in this context. The book is divided into five parts. Part I discusses the fundamental nature of design science and its artifacts, as well as related design research questions and goals. Part II deals with the design cycle, i.e. the creation, design and validation of artifacts based on requirements and stakeholder goals. To elaborate this further, Part III presents the role of conceptual frameworks and theories in design science. Part IV continues with the empirical cycle to investigate artifacts in context, and presents the different elements of research problem analysis, research setup and data analysis. Finally, Part V deals with the practical application of the empirical cycle by presenting in detail various research methods, including observational case studies, case-based and sample-based experiments and technical action research. These main sections are complemented by two generic checklists, one for the design cycle and one for the empirical cycle. The book is written for students as well as academic and industrial researchers in software engineering or information systems. It provides guidelines on how to effectively structure research goals, how to analyze research problems concerning design goals and knowledge questions, how to validate artifact designs and how to empirically investigate artifacts in context – and finally how to present the results of the design cycle as a whole.

Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements. Providing a range of solutions to control and signal processing problems, this book: * Presents a comprehensive introduction to the polynomial systems approach for the solution of H_2 and H_infinity optimal control problems. * Develops robust control design procedures using frequency domain methods. * Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. * Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. * Considers time-varying control and signal processing problems. * Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

An up-to-date guide for using massive amounts of data and novel technologies to design, build, and maintain better systems engineering Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering offers a guide to the recent changes in systems engineering prompted by the current challenging and innovative industrial environment called the Fourth Industrial Revolution—INDUSTRY 4.0. This book contains advanced models, innovative practices, and state-of-the-art research findings on systems engineering. The contributors, an international panel of experts on the topic, explore the key elements in systems engineering that have shifted towards data collection and analytics, available and used in the design and development of systems and also in the later life-cycle stages of use and retirement. The contributors address the issues in a system in which the system involves data in its operation, contrasting with earlier approaches in which data, models, and algorithms were less involved in the function of the system. The book covers a wide range of topics including five systems engineering domains: systems engineering and systems thinking; systems software and process engineering; the digital factory; reliability and maintainability modeling and analytics; and organizational aspects of systems engineering. This important resource: Presents new and advanced approaches, methodologies, and tools for designing, testing, deploying, and maintaining advanced complex systems Explores effective evidence-based risk management practices Describes an integrated approach to safety, reliability, and cyber security based on system theory Discusses entrepreneurship as a multidisciplinary system Emphasizes technical merits of systems engineering concepts by providing technical models Written for systems engineers, Systems Engineering in the Fourth Industrial Revolution offers an up-to-date resource that contains the best practices and most recent research on the topic of systems engineering.

"Information Systems Analysis and Design presents essential knowledge about management information systems development. It is used for four-year university/college students who study information systems analysis and design. Students will learn the information systems development strategies and the process of information systems development. The book emphasizes the key methods of information systems acquisition development, including business process modeling and systems acquisition design. To maintain a well-rounded approach to the topic, both fundamental knowledge about information systems development and hands-on materials are presented. Succinct tutorials for professional systems development project are also included"--