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Title: Automated Process Planning for Five-Axis Point Milling of Sculptured Surfaces
Authors: GENG LIN
Keywords: 5-axis machining, Process planning, Cutter accessiblity, Machining interference, Tool-paths generation, Evolutionary algorithms
Issue Date: 27-Sep-2012
Citation: GENG LIN (2012-09-27). Automated Process Planning for Five-Axis Point Milling of Sculptured Surfaces. ScholarBank@NUS Repository.
Abstract: In this thesis, research efforts for building an automated process planning system for 5-axis point milling of sculpture surfaces (finish cut) are presented. Based on existing research, workflow for process planning was carefully planned out, with optimization and improvements in the following areas: Firstly, a new representation scheme for the accessible posture range of a cutter at a surface point, called boundary posture chain, is proposed. With this new formation, the accessible posture ranges at different surface points are directly comparable, making the fast construction of accessible posture ranges through interpolation possible. Secondly, a novel method for tool-path length estimation for a given cutter and an accessible machining area is proposed to improve an existing multi-cutter selection algorithm. It makes use of neural network (NN) and is shown to be able to achieve more accurate estimation compared with the existing heuristic. Thirdly, methods are proposed to detect and eliminate possible machining interferences during the interpolation process between cutter locations (CLs). Such methods, making use of the enveloping surface of a cutter?s movement, work as remedies for the existing heuristic-based posture assignment process. Finally, evolutionary algorithms (EA) are adopted for posture optimization. Both tool-path smoothness and machining efficiency are taken as optimization objectives while interference avoidance and scallop height tolerance acts as constraints. Two methods are proposed, following an assignment-repairing approach and a direct optimization approach respectively. EA tools of particle swarm optimization (PSO) and genetic algorithm (GA) are applied in these two approaches with satisfactory performance. 5-axis machining of sculpture surfaces is complicated problem with many constraints. The research presented in this thesis is a step made towards a fully automated process planning system to deliver optimal solutions for the problem.
Appears in Collections:Ph.D Theses (Open)

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