Skip to main content
Book cover

Statistics for Chemical and Process Engineers

A Modern Approach

  • Book
  • © 2015

Overview

  • Covers all concepts required by the American Fundamentals of Engineering Examination
  • Helps the reader perform correct data analysis by providing detailed guidance frameworks in addition to the conceptual presentation
  • Emphasizes examples relevant to chemical and process engineers especially those new to statistical analysis
  • Microsoft Excel Templates facilitate the use of the methods presented without requiring the practitioner to have access to specialized software
  • Generalized exposition of results means they can be put to use in the widest range of applications possible
  • Integrative approach to system identification, linear regression and statistical theory helps the reader to understand the similarities and differences in the methods used
  • Includes supplementary material: sn.pub/extras

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 129.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (8 chapters)

Keywords

About this book

A coherent, concise and comprehensive course in the statistics needed for a modern career in chemical engineering; covers all of the concepts required for the American Fundamentals of Engineering examination.

This book shows the reader how to develop and test models, design experiments and analyse data in ways easily applicable through readily available software tools like MS Excel® and MATLAB®. Generalized methods that can be applied irrespective of the tool at hand are a key feature of the text.

The reader is given a detailed framework for statistical procedures covering:

·         data visualization;

·         probability;

·         linear and nonlinear regression;

·         experimental design (including factorial and fractional factorial designs); and

·         dynamic process identification.

Main concepts are illustrated with chemical- and process-engineering-relevant examples that can also serve as the bases for checking any subsequent real implementations. Questions are provided (with solutions available for instructors) to confirm the correct use of numerical techniques, and templates for use in MS Excel and MATLAB can also be downloaded from extras.springer.com.

With its integrative approach to system identification, regression and statistical theory, Statistics for Chemical and Process Engineers provides an excellent means of revision and self-study for chemical and process engineers working in experimental analysis and design in petrochemicals, ceramics, oil and gas, automotive and similar industries and invaluable instruction to advanced undergraduate and graduate students looking to begin a career in the process industries.

Authors and Affiliations

  • Institute of Automation and Complex Systems (AKS), University of Duisburg-Essen, Duisberg, Germany

    Yuri A.W. Shardt

About the author

Prof. Dr. Yuri A. W. Shardt is currently the chair of the Department of Automation Engineering (DE: Fachgebiet Automatisierungstechnik) in the Faculty of Computer Science and Automation (DE: Fakultät Informatik und Automatisierung) at the Technical University of Ilmenau (DE: Technische Universität Ilmenau), working in the fields of big data, including process identification and monitoring with an emphasis on the development and industrial implementation of soft sensors; holistic control, including the development of advanced control strategies for complex industrial process; and the smart world, including such implementations as smart factories, smart home, Industry 4.0, and smart grids. Previously, he worked at the University of Waterloo in the Department of Chemical Engineering and at the University of Duisburg-Essen in the Institute of Control and Complex Systems (DE: Fachgebiet Automatisierungstechnik und komplexe Systeme, AKS) as an Alexander von Humboldt Fellow. He has written 30 papers appearing in such journals as Automatica, Journal of Process Control, IEEE Transactions on Industrial Electronics, and Industrial and Engineering Chemistry Research on topics ranging from system identification, soft sensor development, to process control. He has presented his research at numerous conferences and taught various courses in the intersection between statistics, chemical engineering, process control, EXCEL®, and MATLAB®. Prof. Dr. Shardt completed his doctoral degree under the supervision of Prof. Dr. Biao Huang at the University of Alberta. His thesis examined the methods for extracting valuable data for system identification from data historians for application to soft sensor design. In addition to his academic work, he has spent considerable time in industry working on implementing various process control solutions. He also has interests in linguistics, as well as software internationalisation and localisation.

Bibliographic Information

Publish with us