Readings Newsletter
Become a Readings Member to make your shopping experience even easier.
Sign in or sign up for free!
You’re not far away from qualifying for FREE standard shipping within Australia
You’ve qualified for FREE standard shipping within Australia
The cart is loading…

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
An AI-powered system for monitoring the condition of CNC tools, for early chatter recognition in machine prevents significant losses in the manufacturing industry caused by machine breakdowns. Machine condition monitoring is the practice of observing and tracking specific parameters of a machine in order to detect any major changes that may indicate an impending failure. Continuous machine monitoring enables proactive prevention of failure by detecting and addressing potential issues before they occur. In today's highly competitive environment, manufacturing industries prioritize the production of high-quality products while maximizing productivity. Increasing the Material Removal Rate (MRR) can improve the productivity of various manufacturing industries. This book provides a comprehensive examination of the literature on the phenomena of chatter. Based on this analysis, it has been deduced that researchers have proposed several approaches for identifying and suppressing chatter. However, these strategies have not been widely used in the industry. The primary aim of this book is to offer a methodology for determining the ideal range of process parameters for achieving stable machining with a higher material removal rate. The method encompasses data acquisition, study of sensitive positions to choose appropriate sensor placements, signal pre-processing, feature extraction, feature selection, classification, and optimization techniques. Moreover, in this book both traditional as well as non-traditional (Artificial Intelligence) techniques have been presented. These techniques are being used in industries for achieving better products along with higher productivity.
$9.00 standard shipping within Australia
FREE standard shipping within Australia for orders over $100.00
Express & International shipping calculated at checkout
Stock availability can be subject to change without notice. We recommend calling the shop or contacting our online team to check availability of low stock items. Please see our Shopping Online page for more details.
This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
An AI-powered system for monitoring the condition of CNC tools, for early chatter recognition in machine prevents significant losses in the manufacturing industry caused by machine breakdowns. Machine condition monitoring is the practice of observing and tracking specific parameters of a machine in order to detect any major changes that may indicate an impending failure. Continuous machine monitoring enables proactive prevention of failure by detecting and addressing potential issues before they occur. In today's highly competitive environment, manufacturing industries prioritize the production of high-quality products while maximizing productivity. Increasing the Material Removal Rate (MRR) can improve the productivity of various manufacturing industries. This book provides a comprehensive examination of the literature on the phenomena of chatter. Based on this analysis, it has been deduced that researchers have proposed several approaches for identifying and suppressing chatter. However, these strategies have not been widely used in the industry. The primary aim of this book is to offer a methodology for determining the ideal range of process parameters for achieving stable machining with a higher material removal rate. The method encompasses data acquisition, study of sensitive positions to choose appropriate sensor placements, signal pre-processing, feature extraction, feature selection, classification, and optimization techniques. Moreover, in this book both traditional as well as non-traditional (Artificial Intelligence) techniques have been presented. These techniques are being used in industries for achieving better products along with higher productivity.