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Books on the topic 'Process Automation and Optimization'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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1

M, Colosimo Bianca, and Del Castillo Enrique, eds. Bayesian process monitoring, control and optimization. Chapman and Hall/CRC, 2007.

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2

J, Swetits John, and United States. National Aeronautics and Space Administration., eds. Automation of reverse engineering process in aircraft modeling and related optimization problems: Progress report for the period ended December 1994. Old Dominion Research Foundation, 1994.

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3

Castillo, Enrique Del. Process Optimization. Springer US, 2007. http://dx.doi.org/10.1007/978-0-387-71435-6.

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4

Christie, Alan M. Software Process Automation. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79252-6.

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5

Taulli, Tom. Robotic Process Automation. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6139-2.

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6

Rosenof, Howard P., and Asish Ghosh. Batch Process Automation. Springer US, 1987. http://dx.doi.org/10.1007/978-1-4684-6641-6.

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7

Scheer, August-Wilhelm, Ferri Abolhassan, Wolfram Jost, and Mathias Kirchmer, eds. Business Process Automation. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24702-9.

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8

Koch, Christina, and Stephen Fedtke. Robotic Process Automation. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-61178-4.

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9

Liu, Shu-Jun. Stochastic Averaging and Stochastic Extremum Seeking. Springer London, 2012.

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10

Hofstede, Arthur H. M., Wil M. P. Aalst, Michael Adams, and Nick Russell, eds. Modern Business Process Automation. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-03121-2.

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11

Cichocki, Andrzej, Abdelsalam Helal, Marek Rusinkiewicz, and Darrell Woelk. Workflow and Process Automation. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5677-0.

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12

Hollender, Martin. Collaborative process automation systems. ISA, 2010.

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13

Hollender, Martin. Collaborative process automation systems. ISA, 2010.

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14

Kookos, Ioannis K. Practical Chemical Process Optimization. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11298-0.

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15

R, Tobin Michael, ed. Process characterization and optimization. Addison-Wesley, 1993.

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16

Andersson, Anders. Measurement Technology for Process Automation. CRC Press, 2017. http://dx.doi.org/10.4324/9781315267913.

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17

Koschmider, Agnes, and Stefan Schulte, eds. Blockchain and Robotic Process Automation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81409-0.

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18

Taulli, Tom. The Robotic Process Automation Handbook. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5729-6.

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19

Feldmann, Carsten, ed. Praxishandbuch Robotic Process Automation (RPA). Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-38379-4.

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20

Rijnsdorp, John E. Integrated process control and automation. Elsevier, 1991.

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21

Smeets, Mario Richard, Ralf Jürgen Ostendorf, and Andreas Freßmann. Robotic Process Automation im Einsatz. Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-41956-1.

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22

Smeets, Mario Richard, Andreas Freßmann, and Ralf Jürgen Ostendorf. Robotic Process Automation in Use. Springer Fachmedien Wiesbaden, 2024. http://dx.doi.org/10.1007/978-3-658-45902-4.

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23

Jacek, Jeżowski, ed. Energy optimization in process systems. Elsevier, 2009.

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24

Passino, Kevin M. Biomimicry for Optimization, Control, and Automation. Springer London, Limited, 2005.

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25

Bayesian process monitoring, control, and optimization. Chapman and Hall/CRC Press, 2006.

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26

National Aeronautics and Space Administration (NASA) Staff. Automation of Reverse Engineering Process in Aircraft Modeling and Related Optimization Problems. Independently Published, 2018.

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27

Process Intensification in Chemical Engineering: Design Optimization and Control. Springer London, Limited, 2016.

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28

Combining DataOps, MLOps and DevOps: Outperform Analytics and Software Development with Expert Practices on Process Optimization and Automation. BPB Publications, 2022.

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29

Castillo, Enrique del. Process Optimization. Springer, 2008.

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30

Mehta, Vaishali, Dolly Sharma, Monika Mangla, Anita Gehlot, Rajesh Singh, and Sergio Márquez Sánchez, eds. Challenges and Opportunities for Deep Learning Applications in Industry 4.0. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150360601220101.

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Abstract:

The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the limitations for technical progress is the bottleneck encountered due to the enormous increase in data volume for processing, comprising various formats, semantics, qualities and features. Deep learning enables detection of meaningful features that are difficult to perform using traditional methods. The book takes the reader on a technological voyage of the industry 4.0 space. Chapters highlight recent applications of deep learning and the associated challenges and opportunities it presents for automating industrial processes and smart applications. Chapters introduce the reader to a broad range of topics in deep learning and machine learning. Several deep learning techniques used by industrial professionals are covered, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical project methodology. Readers will find information on the value of deep learning in applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. The book also discusses prospective research directions that focus on the theory and practical applications of deep learning in industrial automation. Therefore, the book aims to serve as a comprehensive reference guide for industrial consultants interested in industry 4.0, and as a handbook for beginners in data science and advanced computer science courses.

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31

Tatjewski, Piotr. Advanced Control of Industrial Processes: Structures and Algorithms. Springer, 2007.

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32

Tatjewski, Piotr. Advanced Control of Industrial Processes: Structures and Algorithms. Springer, 2010.

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33

Czarnecki, Christian, and Peter Fettke, eds. Robotic Process Automation. De Gruyter, 2021. http://dx.doi.org/10.1515/9783110676693.

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34

Process Automation Handbook. Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-282-9.

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35

(Editor), August Wilhelm Scheer, Ferri Abolhassan (Editor), Wolfram Jost (Editor), and Mathias Kirchmer (Editor), eds. Business Process Automation. Springer, 2004.

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36

Christie, Alan M. Software Process Automation. Island Press, 1995.

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37

Quarre, Florian. Robotic Process Automation. O'Reilly Media, Incorporated, 2020.

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38

Rosenof, Howard P. Batch process automation. Van Nostrand Reinhold, 1987.

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39

Chakrawarti, Rajesh Kumar, Sanjaya Kumar Sarangi, and Anand Singh Gadwal. Robotic Process Automation. Wiley & Sons, Incorporated, John, 2023.

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40

Chakrawarti, Rajesh Kumar, Sanjaya Kumar Sarangi, and Anand Singh Gadwal. Robotic Process Automation. Wiley & Sons, Incorporated, John, 2023.

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41

Chakrawarti, Rajesh Kumar, Sanjaya Kumar Sarangi, and Anand Singh Gadwal. Robotic Process Automation. Wiley & Sons, Limited, John, 2023.

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42

Biocatalytic Process Optimization. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-03943-916-4.

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43

Business process optimization. Academica, 2010.

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44

Krstic, Miroslav, and Shu-Jun Liu. Stochastic Averaging and Stochastic Extremum Seeking. Springer, 2014.

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45

Industrial Process Automation Systems. Elsevier, 2015. http://dx.doi.org/10.1016/c2013-0-18954-4.

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46

Hollender, Martin. Collaborative Process Automation Systems. ISA, 2012.

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47

Process Control and Automation. Arcler Education Inc, 2024.

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48

Smith, Gillian. Automation In Process Chemistry. CRC, 2008.

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49

Collaborative process automation systems. ISA, 2010.

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50

Ansari, Helal A. Workflow and Process Automation. Island Press, 1997.

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