Surface Partitioning for 3+2-axis Machining: The application of artificial intelligence algorithms for the machining of complex surfaces

 
9783847301158: Surface Partitioning for 3+2-axis Machining: The application of artificial intelligence algorithms for the machining of complex surfaces
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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.

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Dr. 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 methods for manufacturing. He has participated as a faculty advisor for the Baja SAE, HPV, Aero design and Electraton teams.

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Book Description Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | The application of artificial intelligence algorithms for the machining of complex surfaces | 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. | Format: Paperback | Language/Sprache: english | 176 pp. Seller Inventory # K9783847301158

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Book Description LAP Lambert Academic Publishing Dez 2011, 2011. Taschenbuch. Condition: Neu. 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. Seller Inventory # 9783847301158

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Book Description LAP Lambert Academic Publishing Dez 2011, 2011. Taschenbuch. Condition: Neu. 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. Seller Inventory # 9783847301158

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Book Description LAP Lambert Academic Publishing Dez 2011, 2011. Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand 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. Seller Inventory # 9783847301158

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Book Description LAP Lambert Academic Publishing. Paperback. Condition: New. 176 pages. Dimensions: 8.7in. x 5.9in. x 0.4in.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 CADCAM 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 32-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. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9783847301158

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Book Description LAP Lambert Academic Publishing, Germany, 2011. Paperback. Condition: New. Aufl.. Language: English . Brand New Book. 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. Seller Inventory # KNV9783847301158

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