Feature-Based Automated Tool Path Planning for Discrete Geometry

Doctoral Candidate Name: 
Fei Shen
Mechanical Engineering

CNC machining is a critical manufacturing technology in effectively all modern products. Any improvement in efficiency or automation that reduces the cost of CNC machining is of tremendous value to the manufacturing industry. One of the most time-consuming steps in CNC machining, especially in a high-mix low-volume scenario, such as prototyping, is the current tool path planning workflow. The current industrial state of Computer-Aided Manufacturing (CAM) tools used to generate toolpaths requires highly trained CNC programmers. Typically, programmers manually select the features to be machined, the tools to use for each feature, the specific tool paths topology, and the feeds and speeds.

In the research community, there is a lot of focus on the automation of the tool path planning process, aiming to reduce the significant effort required to generate toolpaths. Researchers have developed novel feature recognition techniques, automated tool path generation methods, and tool selection algorithms. However, these methods all come with certain caveats and limitations. Some only work on continuous geometries. Others only work on certain feature types.

This dissertation introduces a feature based automated tool path planning system with the focus on implementing robust and generalized algorithms that work on arbitrary geometries with the full range of features based on discrete geometry. Support for discrete geometry is valuable because there are many situations where only discrete geometry is available as in models generated from 3D scanning systems. Specifically, a robust region segmentation technique is developed to simplify machining feature recognition from discrete geometry. Once the features are recognized, an automated optimal cutter set selection approach aiming at a minimum machining time is proposed to improve the machining efficiency for arbitrary features. Additionally, an automated deburring tool path planning method is introduced to eliminate the manual edge deburring and specifically to work with 3D discrete geometry. With the robust and automated algorithms as a solid foundation, a fully automated tool path planning system with limited human interactions is built and demonstrated on a series of parts with complex intersecting features. The net result is a complete 3D CAM process that goes from geometry to G-code in less than 1 minute.

Defense Date and Time: 
Wednesday, April 6, 2022 - 1:00pm
Defense Location: 
Duke Hall, Room 308
Committee Chair's Name: 
Dr. Joshua Tarbutton, Dr. Edward Morse
Committee Members: 
Dr. Angela Allen, Dr. Harish Cherukuri, Dr. Yuri Godin