Next Generation Machining Simulation Technologies for Complete and Efficient Process Validation

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Machining simulation is essential to modern Computer Numerical Control (CNC) machining operations. It is used to validate whether the machining commands to be executed by a CNC machine tool are generated without errors and able to produce the desired part geometry correctly. Erroneous machining commands produce defective parts, or worse, damage the machines due to collision, leading to a major loss of productivity and profits. The long-term objective of the proposed research program is to develop enabling technologies that are fundamental to the creation of a complete, efficient and accurate virtual machining system. Planned machining processes can then be validated in the virtual simulation environment prior to the implementation on a physical CNC machine tool. Accuracy is a crucial requirement of such simulation. Efficient simulation execution is equally critical as simulating the machining process of a geometrically complex part can take an enormous amount of time. However, the existing technologies have not overcome the challenges. They either produce inaccurate results or are extremely slow in processing. Moreover, they only offer partial simulation solutions - for either machined part geometry or collision detection. In the next five years, my students and I will develop a complete machining simulation solution for 5-axis milling that considers both in-process workpiece modeling and collision detection. We will maximize the machining simulation efficiency using a multi-level voxel modeling method so that an accurate simulation can be completed in minutes instead of hours or even days. Our research group has a worldwide reputation as a leader in CNC machining research. With our expertise in both CNC machining and product modeling, we have developed a novel, patent-pending geometric modeling method to compute the machined part geometry with both accuracy and efficiency. We will build on this method to develop a unified, efficient and accurate geometric modeling method for a complete machining process simulation system that covers both tool-workpiece collision detection and tool-machine collision detection. Two PhD students, four Master's students, five undergraduate students and a part-time research associate will be trained to build the proposed 5-axis milling simulation system. I have developed a recruitment plan to attract female students to join the team by reaching out to female undergraduate students at UBC. My students are encouraged to attend the equity, diversity and inclusion training sessions at UBC to increase awareness and help create an inclusive research environment in my lab. Canadian aerospace and automotive industries, with $112.6B/year in sales, have invested substantially in CNC machining and produced millions of parts annually using CNC machine tools. The proposed research will benefit these manufacturers and enable them to quickly develop and validate the CNC machining processes and produce high-quality machined parts.