Global obstacle avoidance and minimum workpiece setups in five-axis machining

• Classification of different types of obstacles encountered in five-axis NC machining.
• Efficient numerical algorithms on how to represent dynamic obstacles.
• Efficient computing of feasible regions considering all types of obstacles.
• A heuristic optimization algorithm for finding the best workpiece setup.
• A thorough analysis of both static and dynamic obstacles.

The state-of-the-art tool path computation algorithms for five-axis machining consider only the workpiece and clamping device for collision avoidance. However, in a real five-axis machining process, there are many other types of obstacles beyond workpiece and clamps that the tool assembly must avoid, e.g., sensors and other intrusive devices. In such cases, the only solution at present is by means of computer simulation of the machining process after the tool path has been computed. If collision is found, it requires re-computing the tool path and/or changing the setup of the workpiece. This process is then re-iterated until all the collisions are resolved. As a result, the process is time consuming and requires excessive human intervention. In this paper, we present rigorous analyses of the obstacles in five-axis machining and propose efficient numerical algorithms for calculating and representing them. Using our results, the obstacle-free tool orientations can be determined completely at the tool path planning stage, rather than relying on the simulation afterward. In addition, as a direct application of our mathematical modeling, we present a heuristic-based solution to the optimal workpiece setups problem: finding a minimum number of workpiece setups for an arbitrary sculpture part surface so that it can be machined completely on a given five-axis machine without colliding with the obstacles. We use orthogonal table–table five-axis machines as an example and work out a numerical experiment using the proposed solution.