Handbook of Industrial and Systems Engineering (Industrial Innovation Series)

Abstract : Responding to the demand by researchers and practitioners for a comprehensive reference, Handbook of Industrial and Systems Engineering offers full and easy access to a wide range of industrial and systems engineering tools and techniques in a concise format. Providing state of the art coverage from more than 40 contributing authors, many of whom are “rising stars” in this area, this volume emphasizes systems engineering aspects and expands beyond the topics found in the existing references in this field.

The handbook is a one-stop source for industrial and systems engineering. It introduces new technologies, offers a systems integration approach, and provides coverage of information engineering. Part I delivers a general introduction featuring references to the origin of industrial engineering and its ties to the Industrial Revolution. Parts II and III cover the fundamentals of industrial and systems engineering. Part IV contains chapters on manufacturing and production systems, while part V addresses new technologies. The book concludes with general applications of both industrial and systems engineering.

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Algorithmic Aspects of Wireless Sensor Networks

This book constitutes the reviewed proceedings of the Third International Workshop on Algorithmic Aspects of Wireless Sensor Networks, ALGOSENSORS 2007, held in Wroclaw, Poland, July 14, 2007, in association with ICALP 2007.The 11 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 26 submissions; they are fully revised to incorporate reviewers' comments and discussions at the workshop. Topics addressed are foundational and algorithmic aspects of the wireless sensor networks research. In particular, ALGOSENSORS focuses on abstract models, complexity-theoretic results and lower-bounds, as well as the design and analysis of algorithms for wireless sensor networks.

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Artificial Neural Networks - Industrial and Control Engineering Applications

Edited by: Kenji Suzuki



ISBN 978-953-307-220-3, Hard cover, 478 pages

Publisher: InTech

Publication date: April 2011

Artificial neural
networks may probably be the single most successful technology in the
last two decades which has been widely used in a large variety of
applications. The purpose of this book is to provide recent advances of
artificial neural networks in industrial and control engineering
applications. The book begins with a review of applications of
artificial neural networks in textile industries. Particular
applications in textile industries follow. Parts continue with
applications in materials science and industry such as material
identification, and estimation of material property and state, food
industry such as meat, electric and power industry such as batteries and
power systems, mechanical engineering such as engines and machines, and
control and robotic engineering such as system control and
identification, fault diagnosis systems, and robot manipulation. Thus,
this book will be a fundamental source of recent advances and
applications of artificial neural networks in industrial and control
engineering areas. The target audience includes professors and students
in engineering schools, and researchers and engineers in industries.

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Multivariate Statistical Process Control with Industrial Application

This applied, self-contained text provides detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T"2" statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. The authors, leading researchers in this area who have developed major software for this type of charting procedure, provide valuable insight into T"2" statistic. Intentionally including only a minimal amount of theory, they lead readers through the construction and monitoring phases of the T"2" control statistic using numerous industrial examples taken primarily from the chemical and power industries. These examples are applied to the construction of historical data sets to serve as a point of reference for the control procedure and are also applied to the monitoring phase where emphasis is placed on signal location and interpretation in terms of the process variables. Specifically devoted to the T"2" methodology, Multivariate Statistical Process Control: With Industrial Applications is the only book available that concisely and thoroughly presents such topics as how to construct a historical data set; how to check the necessary assumptions used with this procedure; how to chart the T"2" statistic; how to interpret its signals; how to use the chart in the presence of autocorrelated data; and how to apply the procedure to batch processes. Unique and easy-to-apply software specifically designed for the application of a T"2" control procedure is included.

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Diagnosis of Process Nonlinearities and Valve Stiction Book

In this book Higher Order Statistical theory is used to develop indices for detecting and quantifying signal non-Gaussianity and nonlinearity. These indices are used to diagnose the causes of poor control loop performance.

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