GPU Accelerated Process Planning For CNC-Machined Parts:Industrial Components to Bone Implants
Department of Industrial and Manufacturing Systems Engineering, Iowa State University of Science and Technology, USA
@article{joshigpu,
title={GPU Accelerated Process Planning For CNC-Machined Parts: Industrial Components to Bone Implants},
author={Joshi, Ashish and Frank, Matthew}
}
For manufacturing a part using conventional 3-Axis CNC machining process, one must determine a set of machining orientations. Generally this process planning task is carried out manually by the machinist, considering decision parameters such as part visibility, machinability, machining depths, tool geometry, etc. In this work, we modelled this as a Linear optimization problem; the solution to which is a set of machining orientations. The solution methodology employs a Greedy algorithm and a Heuristic Simulated Annealing (SA) approach in order to get a globally optimal solution set of machining orientations. The algorithms yielding are ported process on planning a GPU(Tesla-C2075) parameters [1][2] (% Visibility and Machinability). The input to these algorithms is a set of 2D slices created from polyhedral .STL files. The software implementation is done in Visual Studio 2010 using C++ and CUDA C.
March 21, 2014 by hgpu
