Roman Armando (9 results)

Soft Cover. Condition: Fine.

Softcover. Condition: Good. First Edition; First Printing. Paperback with cover wear. 122 pages, unmarked. ISBN 9786070044199. Signed by 3 contributors ; ECR A4A; 8vo 8" - 9" tall; 122 pages; Signed by Collection of Signatures.

Encuadernación de tapa blanda. Condition: Bien. Roman (illustrator). Todos nuestros libros son de segunda mano.

Taschenbuch. Condition: Neu. Surface Partitioning for 3+2-axis Machining | The application of artificial intelligence algorithms for the machining of complex surfaces | Armando Roman | Taschenbuch | 176 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783847301158 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Despite the inbuilt advantages offered by 5-axis machining, the manufacturing industry has not widely adopted this technology due to the high cost of machines and insufficient support from CAD/CAM systems. Companies are used to 3-axis machining and the operators are in many cases not yet ready for 5-axis machining in terms of training and programming. An effective solution for this 5 axis problem is a graduated migration through the use of 3+2-axis machining. The objective of this research is to develop and implement a machining technique that uses the simplicity of 3-axis tool positioning and the flexibility of 5-axis tool orientation, to machine complex surfaces. This work presents the application of well known methods from Pattern Recognition and newly developed methods by the current author that were adapted for surface machining. This work includes an explanation of the procedures required to determine an appropriate tool orientation, feed direction, tool path trajectory and tool parameters for patch-by-patch machining. These parameters are determined independently for each patch and aim at reducing the time required to machine a surface while maintaining the surface specific. 176 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Roman ArmandoDr. Armando Roman is a graduate from the University of Waterloo and currently the Director of Mechatronics at Tec de Monterrey Campus Guadalajara. His reseach interests are in the application of artificial intelligence m.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Despite the inbuilt advantages offered by 5-axis machining, the manufacturing industry has not widely adopted this technology due to the high cost of machines and insufficient support from CAD/CAM systems. Companies are used to 3-axis machining and the operators are in many cases not yet ready for 5-axis machining in terms of training and programming. An effective solution for this 5 axis problem is a graduated migration through the use of 3+2-axis machining. The objective of this research is to develop and implement a machining technique that uses the simplicity of 3-axis tool positioning and the flexibility of 5-axis tool orientation, to machine complex surfaces. This work presents the application of well known methods from Pattern Recognition and newly developed methods by the current author that were adapted for surface machining. This work includes an explanation of the procedures required to determine an appropriate tool orientation, feed direction, tool path trajectory and tool parameters for patch-by-patch machining. These parameters are determined independently for each patch and aim at reducing the time required to machine a surface while maintaining the surface specific.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 176 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Despite the inbuilt advantages offered by 5-axis machining, the manufacturing industry has not widely adopted this technology due to the high cost of machines and insufficient support from CAD/CAM systems. Companies are used to 3-axis machining and the operators are in many cases not yet ready for 5-axis machining in terms of training and programming. An effective solution for this 5 axis problem is a graduated migration through the use of 3+2-axis machining. The objective of this research is to develop and implement a machining technique that uses the simplicity of 3-axis tool positioning and the flexibility of 5-axis tool orientation, to machine complex surfaces. This work presents the application of well known methods from Pattern Recognition and newly developed methods by the current author that were adapted for surface machining. This work includes an explanation of the procedures required to determine an appropriate tool orientation, feed direction, tool path trajectory and tool parameters for patch-by-patch machining. These parameters are determined independently for each patch and aim at reducing the time required to machine a surface while maintaining the surface specific.