Fundamentals of Artificial Neural Network for Manufacturing Engineer using Python Language with Gui Development and Executable Conversion

Authors

Yupiter Hp Manurung
Suhaila Abd Halim
Low Cheng Yee

Keywords:

Neural, method, data analytic, development

Synopsis

This book is accomplished as result of a long term local and international collaboration between Smart Manufacturing Research Institute (SMRI) at Universiti Teknologi MARA in Shah Alam, Faculty of Mechanical and Manufacturing Enginering at Universiti Tun Hussein Onn Malaysia in Batu Pahat, University of Applied Sciences in Osnabrück, Germany and Fraunhofer Institute for Mechatronic Systems Design in Paderborn, Germany. The structure of this book is as follows: Chapter 1 discusses the overview of artificial intelligence, artificial neural networks, and the basic ideas behind machine learning. A perceptron concept is presented as a simple computing element with selected activation function. Some standard loss functions are introduced with its mathematical equations. This chapter also outlines the standard backpropagation method and Levenberg-Marquardt algorithm. At the end of the chapter, a step-by-step backpropagation example is described to work through simple neural networks' mathematical ideas gently. Chapter 2 introduces python programming languages. Some of the python applications are shown. In addition, Package Management System is also briefly presented. Chapter 3 deliberates essential information on Jupyter and Spyder integrated development environment to code the ANN program. Chapter 4 is aimed to design graphical user interface using Qt designer and to add functionalities to GUI project. This chapter teaches how to use different widgets such as QLabel, QCheckBox, QLineEdit, etc. Chapter 5 provides an overview of the ANN application in the manufacturing processes. Some of the applications are outlined in the chapter. The case study of resistance spot welding with ANN application is explained following quality issue. The dataset acquired for the training of the ANN model is shown in this chapter. The ANN applications produced the result, and the advanced recommendation of the ANN is proposed. Chapter 6 shares the future outlook of artificial intelligence application in manufacturing data analytic.

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References

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Published

1 October 2024

Details about the available publication format: PDF

PDF

ISBN-13 (15)

978-629-490-045-5

Physical Dimensions

How to Cite

Yupiter Hp Manurung, Suhaila Abd Halim, & Low Cheng Yee. (2024). Fundamentals of Artificial Neural Network for Manufacturing Engineer using Python Language with Gui Development and Executable Conversion. Penerbit UTHM. https://publisher.uthm.edu.my/omp/index.php/penerbituthm/catalog/book/431