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Advanced Numerical Methods to Optimize Cutting Operations of Five Axis Milling Machines: Springer Series in Advanced Manufacturing

Autor Stanislav S. Makhanov, Weerachai Anotaipaiboon
en Limba Engleză Hardback – 3 apr 2007

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Specificații

ISBN-13: 9783540711209
ISBN-10: 3540711201
Pagini: 228
Ilustrații: XVII, 206 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.5 kg
Ediția:2007
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Springer Series in Advanced Manufacturing

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

to Five-Axis NC Machining.- Fundamental Issues in Tool Path Planning.- Space-Filling Curve Tool Paths.- Tool Paths in Adaptive Curvilinear Coordinates.- Optimization of Rotations.- Theory of Optimal Setup for Five-Axis NC Machining.

Recenzii

From the reviews:
"The book can be used as introductory material in a university CAM course and … appropriate for R&D at the levels of undergraduate and graduate university programs and in corporations. … it serve as an entry point to the subject for mathematicians looking for new applications." (Michael Bieterman, SIAM Review, Vol. 50 (2), 2008)

Textul de pe ultima copertă

The book presents new optimization algorithms designed to improve the efficiency of tool paths for five-axis NC machining of sculptured surfaces. The book introduces the reader to fundamental issues involved in the tool path planning such as the kinematics of five-axis machines, types of 5 axis machines, part surface representation, machining strips, optimal tool orientation, gouging avoidance and forward step error. It also introduces new methods of optimization based on research conducted by the authors, including schemes performed in the spatial domain, angular domain as well as procedures to optimize the initial setup. The book can be used by undergraduate and graduate students and researchers in the field of NC machining and CAD/CAM as well as by the corporate research groups for advanced optimization of cutting operations.

Caracteristici

Simultaneous Localization and Mapping (SLAM) is an extremely active reseach area sometimes referred to as the "holy grail" of mobile robotics Covers both the structure of the SLAM problem in general and proposes a new extremely efficient approach Includes supplementary material: sn.pub/extras