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Mechanics, dynamics and stability of turn-milling operations Comak, Alptunc
Abstract
Recent turn-milling machine tools are capable of carrying out turning, drilling, boring, milling and grinding operations simultaneously, hence they are widely used in industry to produce complex parts in a single set-up. Turn-milling machines have translational axes with a high speed spindle to hold the cutting tool and a low speed spindle to carry the workpiece. The resulting five-axis turn-milling machines can machine parts with complex curved tool paths. This thesis presents the mechanics and dynamics of turn-milling operations to predict cutting forces, torque, power, vibrations, chatter stability and dimensional surface errors in the virtual environment. First, the kinematics of five-axis turn milling operation is modeled using homogenous transformations. The engagement of rotating-moving tool with the rotating workpiece is identified using a commercial graphics system, and used in predicting the chip thickness distribution. The relative vibrations between the tool and workpiece are modeled, and superposed on the chip thickness in the engagement zone. Unlike in regular turning and milling operations with a single spindle which leads to a single and constant delay, turn milling has two time delays contributed by two rotating spindles and three translational feed drives. The regenerative chip thickness with dual delay is used to predict the cutting forces at tool-workpiece engagement zone, which are transformed to three Cartesian directions of the machine. The resulting coupled differential equations with two delays and time periodic coefficients are solved in the semi-discrete time domain to predict chatter stability, cutting forces, vibrations, torque, power and dimensional surface errors simultaneously. The thesis presents the first comprehensive digital model of turn milling operations in the literature, and can be used to predict the most productive cutting conditions ahead of costly physical trials currently practiced in the industry.
Item Metadata
Title |
Mechanics, dynamics and stability of turn-milling operations
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2018
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Description |
Recent turn-milling machine tools are capable of carrying out turning, drilling, boring, milling and grinding operations simultaneously, hence they are widely used in industry to produce complex parts in a single set-up. Turn-milling machines have translational axes with a high speed spindle to hold the cutting tool and a low speed spindle to carry the workpiece. The resulting five-axis turn-milling machines can machine parts with complex curved tool paths. This thesis presents the mechanics and dynamics of turn-milling operations to predict cutting forces, torque, power, vibrations, chatter stability and dimensional surface errors in the virtual environment.
First, the kinematics of five-axis turn milling operation is modeled using homogenous transformations. The engagement of rotating-moving tool with the rotating workpiece is identified using a commercial graphics system, and used in predicting the chip thickness distribution. The relative vibrations between the tool and workpiece are modeled, and superposed on the chip thickness in the engagement zone. Unlike in regular turning and milling operations with a single spindle which leads to a single and constant delay, turn milling has two time delays contributed by two rotating spindles and three translational feed drives. The regenerative chip thickness with dual delay is used to predict the cutting forces at tool-workpiece engagement zone, which are transformed to three Cartesian directions of the machine. The resulting coupled differential equations with two delays and time periodic coefficients are solved in the semi-discrete time domain to predict chatter stability, cutting forces, vibrations, torque, power and dimensional surface errors simultaneously.
The thesis presents the first comprehensive digital model of turn milling operations in the literature, and can be used to predict the most productive cutting conditions ahead of costly physical trials currently practiced in the industry.
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Genre | |
Type | |
Language |
eng
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Date Available |
2018-07-16
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0368954
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2018-09
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International