THESIS
2022
1 online resource (xi, 61 pages) : illustrations (some color)
Abstract
Geometric modeling of the in-process workpiece (IPW) and collision detection are two important parts in simulating an additive manufacturing (AM) process. The desire of producing product having more complex shape and feature pushes the development of multi-axis AM in recent years. The manufacturing process is becoming more complicated and difficult to simulate. Many geometric modeling and collision detection methods have been proposed and applied in machining simulation, but they cannot be directly applied to simulating AM process. There is demand for new geometric modeling and collision detection method particularly used for AM, which is accurate, efficient, and robust.
This thesis presents a novel IPW generation method to model the IPW in AM, taking G-code file as the input. It is the...[
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Geometric modeling of the in-process workpiece (IPW) and collision detection are two important parts in simulating an additive manufacturing (AM) process. The desire of producing product having more complex shape and feature pushes the development of multi-axis AM in recent years. The manufacturing process is becoming more complicated and difficult to simulate. Many geometric modeling and collision detection methods have been proposed and applied in machining simulation, but they cannot be directly applied to simulating AM process. There is demand for new geometric modeling and collision detection method particularly used for AM, which is accurate, efficient, and robust.
This thesis presents a novel IPW generation method to model the IPW in AM, taking G-code file as the input. It is the first time for an IPW modeling method considering the amount of material deposited, so a more accurate IPW can be obtained by this method. A new data structure of voxel model is introduced in this thesis making combination of two voxel models possible. With the new data structure, IPW can be stored in pieces and then be retrieved back when it is needed. It helps reducing memory consumption of IPW storage and improves the efficiency of constructing and visualizing the IPW. Result shows that the IPW at every step of the manufacturing process can be obtained and visualized efficiently.
This thesis also presents a novel collision detection algorithm detecting interference between the IPW and the nozzle of the AM machine. A robust and accurate board phase algorithm is introduced in the new method based on the nature of the AM process which helps increasing the efficiency of the collision detection process. Experiment result shows that it is faster than the existing collision detection methods.
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