Multi-axis additive manufacturing (AM) varies printing direction to deposit material for model fabrication and processes better surface quality and less support structure comparing with conventional 3-axis AM. Industrial 6R robotic arm as a flexible and accurate manipulator fits demand of multi-axis AM for performing multi-axis motion. Meanwhile, there exist problems in cooperating robotic arm for AM, like jerky and unstable motion for tiny movement in printing process and slow printing motion. This research develops a robotic multi-axis system which consists of a robust XY-table and a 6R robotic arm to optimize for the problem. The process planning for multi-axis AM is also presented.

With system design for motion redundancy, it improves precision and motion smoothness in the...[ Read more ]

Multi-axis additive manufacturing (AM) varies printing direction to deposit material for model fabrication and processes better surface quality and less support structure comparing with conventional 3-axis AM. Industrial 6R robotic arm as a flexible and accurate manipulator fits demand of multi-axis AM for performing multi-axis motion. Meanwhile, there exist problems in cooperating robotic arm for AM, like jerky and unstable motion for tiny movement in printing process and slow printing motion. This research develops a robotic multi-axis system which consists of a robust XY-table and a 6R robotic arm to optimize for the problem. The process planning for multi-axis AM is also presented.

With system design for motion redundancy, it improves precision and motion smoothness in the fabrication process. Utilizing the translational and rotational motion redundancy, different slicing geometries of model for fabrication is optimized. To compensate the assembly error between sub-systems, a calibration method based on probing is used. A Computer Numerical Control (CNC) controller is built to cooperate with machine kinematics and motion redundancy for planning and control. In planning process, commands (path) are look-ahead and pre-loaded. With a circular blending function, trajectory blending is done on task space to blend both the position and orientation of the tool for path and hence achieve motion continuity. Control of junction deviation is introduced into blending process to contain the inevitable error in blending. Feed rate scheduling are then done to plan for the actual speed of the tool according to machine capability and process need.

Finally, basic topological function serving the Computer Aided Manufacturing (CAM) for multi-axis AM is presented in attempt to generalize existing slicing and tool path generation algorithm. A slicing procedure for multi-axis AM is introduced which utilizes topological function and tools. Multiple state-of-the-arts slicing algorithm are repeated and classified into slicing geometry type to cooperate with other basic slicing procedure. Printing experiment is done to validate the effectiveness of different method for multi-axis AM.