Automatic planning and programming for five-axis sculptured surface machining
Abstract
In modern product design, sculptured surfaces are commonly used for functional and artistic shape. They are usually made from a mold. Sculptured surface mold cavities are difficult to machine manually due to their complex shape and irregular surface curvature distribution. Manually operation planning for sculptured surface machining is known to be error-prone and inefficient, requiring considerable checking, verification, and rework. Five-axis machining has been recognized for its high machining productivity and better machining quality, and it is gaining more attentions in industry. However, the programming of five-axis machining is very difficult due to the complex cutter movements simultaneously along the machine's five axes. This research focuses on developing an effective and systematic methodology to analyze sculptured surface design, evaluate machining feasibility by geometric constraints, and extract information for tool selection. Some issues considered are the surface interrogation, automatic cutter selection, analysis of machined surface quality, avoidance of both global tool interference and local gouging. A maximum effective cutting radius approach has been proposed for the automatic cutter selection. Tool approach feasibility checking is a complex operation. A two-phase approach is proposed to solve the problem. First, control polygon approximation which is a tighter constraint is used to detect potential conflicts. If a surface area fails the test, an exact surface checking approach is used to confirm the infeasibility. Error-free cutter paths are generated based on local as well as global machining constraints. A complete operation plan and the cutter path can be automatically generated from the CAD part design. The machining infeasibility can be fed back to the designer for further design modification. The proposed methodology has been implemented as a software called CASCAM-II system and is being integrated into the QTC system, an integrated design and manufacturing system developed in the Engineering Research Center for Intelligent Manufacturing Systems at Purdue University.
Degree
Ph.D.
Advisors
Chang, Purdue University.
Subject Area
Industrial engineering|Mechanical engineering|Automotive materials
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