Machining of Hard Materials : A Comprehensive Approach to Experimentation, Modeling and Optimization / by Manjunath Patel G. C., Ganesh R. Chate, Mahesh B. Parappagoudar, Kapil Gupta.
By: Patel G. C., Manjunath, autor
Contributor(s): SpringerLink (Online service)
| Chate, Ganesh R., autor
| Parappagoudar, Mahesh B, autor
| Gupta, Kapil, autor
Material type:
E-bookSeries: (Manufacturing and Surface Engineering, 2365-8223); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing, 2020Edition: First edition 2020.Description: 1 recurso en línea (IX, 129 páginas) : 39 ilustraciones, 19 ilustraciones a color.ISBN: 9783030401023.Subject: Control automático
In:
Springer eBooksAbstract: This book presents the potential applications of hard materials as well as the latest trends and challenges in machining hard materials. Models for online monitoring to adjust parameters to obtain desired machining characteristics (i.e. reverse modelling) are discussed in this book. The conflicting requirements (i.e. maximize: material removal rate, roundness and minimize: surface roughness, dimensional ovality, co axiality, tool wear) in machining for industry personal is solved using advanced optimization tools. In addition, the framework for experimental modelling, predictive physic-based forward and reverse process models and optimization for better machining characteristics applicable to industry are proposed.
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
|
Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | TJ1185 2020 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.22042115 |
This book presents the potential applications of hard materials as well as the latest trends and challenges in machining hard materials. Models for online monitoring to adjust parameters to obtain desired machining characteristics (i.e. reverse modelling) are discussed in this book. The conflicting requirements (i.e. maximize: material removal rate, roundness and minimize: surface roughness, dimensional ovality, co axiality, tool wear) in machining for industry personal is solved using advanced optimization tools. In addition, the framework for experimental modelling, predictive physic-based forward and reverse process models and optimization for better machining characteristics applicable to industry are proposed.
There are no comments on this title.