Synopsis
This book presents a methodology for manufacturing process signature analysis, which aims to enhance process control systems through data analysis. The author argues that improving control systems involves collecting more information about the process and using it effectively. The book proposes a three-step analysis method, which consists of feature extraction, feature selection, and classification, to establish a relationship between the collected information (process signatures) and the quality of the process output. This relationship can be used for online monitoring and control. The book covers the advantages and limitations of various signature analysis tools, ranging from statistical process control to artificial neural networks. The author emphasizes the importance of feature selection in reducing the complexity of classification problems and discusses different feature selection schemes. One of the key contributions is the use of the first layer weights in a neural network topology to identify the most useful components of the input signature. The book concludes by exploring future research directions, highlighting the need for accurate quality metrics, effective sensor selection, and efficient neural network training algorithms. Overall, this book provides a comprehensive overview of process signature analysis and its application in manufacturing process monitoring and control.
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A Methodology for Manufacturing Process Signature Analysis (Classic Reprint)
Print on DemandSeller: Forgotten Books, London, United Kingdom
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Paperback. Condition: New. Print on Demand. This book presents a methodology for manufacturing process signature analysis, which aims to enhance process control systems through data analysis. The author argues that improving control systems involves collecting more information about the process and using it effectively. The book proposes a three-step analysis method, which consists of feature extraction, feature selection, and classification, to establish a relationship between the collected information (process signatures) and the quality of the process output. This relationship can be used for online monitoring and control. The book covers the advantages and limitations of various signature analysis tools, ranging from statistical process control to artificial neural networks. The author emphasizes the importance of feature selection in reducing the complexity of classification problems and discusses different feature selection schemes. One of the key contributions is the use of the first layer weights in a neural network topology to identify the most useful components of the input signature. The book concludes by exploring future research directions, highlighting the need for accurate quality metrics, effective sensor selection, and efficient neural network training algorithms. Overall, this book provides a comprehensive overview of process signature analysis and its application in manufacturing process monitoring and control. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781332269860_0
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A Methodology for Manufacturing Process Signature Analysis Classic Reprint
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781332269860
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A Methodology for Manufacturing Process Signature Analysis Classic Reprint
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781332269860
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