Machining of Hard Materials : A Comprehensive Approach to Experimentation, Modeling and Optimization
Patel G. C., Manjunath
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. - First edition 2020. - 1 recurso en línea (IX, 129 páginas) 39 ilustraciones, 19 ilustraciones a color - Manufacturing and Surface Engineering 2365-8223 Engineering (Springer-11647) .
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.
9783030401023
10.1007/978-3-030-40102-3 doi
Control automático
TJ1185 / 2020 EB
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. - First edition 2020. - 1 recurso en línea (IX, 129 páginas) 39 ilustraciones, 19 ilustraciones a color - Manufacturing and Surface Engineering 2365-8223 Engineering (Springer-11647) .
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.
9783030401023
10.1007/978-3-030-40102-3 doi
Control automático
TJ1185 / 2020 EB