The Woodruff School

SUMMARY

Voxel-based computer-aided manufacturing (CAM) software has shown great potential in both creating machining plans for highly complex parts and performing realistic simulations of material removal that would be impractical with current industrial CAM systems. The created plans are translated by the CAM system into a format readable by the machine, known as G-Code, which consists of points and maximum velocities that the machine should follow in order to trace out the desired path. Specifying toolpaths to the machine in G-Code has a number of limitations: first, many commands are machine specific, which causes compatibility issues between the CAM system and the CNC; second, translating a toolpath into G-Code causes a loss of valuable process control data between the CAM system and the CNC; and third, the use of G-Code forces the CNC to spend valuable compute cycles performing online trajectory planning using a worst-case approach that can prevent the cutting tool from reaching its programmed maximum velocity. To overcome the limitations present in G-Code programming, this research develops and evaluates a new solution to offline trajectory planning and control that is enables a CNC machine tool to follow a densely-sampled toolpath (such as one created from a voxel model) at the kinematic limits of each axis. Additionally, the proposed approach will allow for the communication of densely-sampled motion trajectories that would be impossible with standard G-Code. The contributions of this work are as follows: first, a generalized framework and accompanying control system for direct transmission of dense data to and from the machine tool’s servo controllers directly from a voxel-based CAM system is developed; second, a reference implementation of this approach is performed on an open-source CNC platform known as Machinekit; third, near-realtime simulation and analysis capabilities from within the CAM system are developed and discussed; and fourth, the accuracy of motion realizable by the new control system is validated using complex toolpaths created from the CAM system and performance is compared to the standard G-Code programming method.

SUBJECT:	Ph.D. Dissertation Defense

BY:	David Lynn

TIME:	Tuesday, February 12, 2019, 9:00 a.m.

PLACE:	GTMI (formerly MaRC), 114

TITLE:	Direct Servo Control of Positional Derivatives for 5-Axis CNC Machine Tools Using Densely-Sampled Toolpaths

COMMITTEE:	Dr. Thomas Kurfess, Chair (ME) Dr. Christopher Saldana (ME) Dr. Tommy Tucker (Industry) Dr. Jarek Rossignac (CS) Dr. Cassandra Telenko (ME) Dr. Moneer Helu (NIST)

SUMMARY Voxel-based computer-aided manufacturing (CAM) software has shown great potential in both creating machining plans for highly complex parts and performing realistic simulations of material removal that would be impractical with current industrial CAM systems. The created plans are translated by the CAM system into a format readable by the machine, known as G-Code, which consists of points and maximum velocities that the machine should follow in order to trace out the desired path. Specifying toolpaths to the machine in G-Code has a number of limitations: first, many commands are machine specific, which causes compatibility issues between the CAM system and the CNC; second, translating a toolpath into G-Code causes a loss of valuable process control data between the CAM system and the CNC; and third, the use of G-Code forces the CNC to spend valuable compute cycles performing online trajectory planning using a worst-case approach that can prevent the cutting tool from reaching its programmed maximum velocity. To overcome the limitations present in G-Code programming, this research develops and evaluates a new solution to offline trajectory planning and control that is enables a CNC machine tool to follow a densely-sampled toolpath (such as one created from a voxel model) at the kinematic limits of each axis. Additionally, the proposed approach will allow for the communication of densely-sampled motion trajectories that would be impossible with standard G-Code. The contributions of this work are as follows: first, a generalized framework and accompanying control system for direct transmission of dense data to and from the machine tool’s servo controllers directly from a voxel-based CAM system is developed; second, a reference implementation of this approach is performed on an open-source CNC platform known as Machinekit; third, near-realtime simulation and analysis capabilities from within the CAM system are developed and discussed; and fourth, the accuracy of motion realizable by the new control system is validated using complex toolpaths created from the CAM system and performance is compared to the standard G-Code programming method.