Chapter

Tool Path Planning for 5-Axis Flank Milling Based on Dynamic Programming Techniques

DOI: 10.1007/978-3-540-79246-8_49
Source: DBLP

ABSTRACT This paper proposes a novel computation method for tool path planning in 5-axis flank milling of ruled surfaces. This method
converts the path planning (a geometry problem) into a curve matching task (a mathematical programming problem). Discrete
dynamic programming techniques are applied to obtain the optimal matching with machining error as the objective function.
Each matching line corresponds to a cutter location and the tool orientation at the location. An approximating method based
on z-buffer is developed for a quick estimation of the error. A set of parameters is allowed to vary in the optimization,
thus generating the optimal tool paths in different conditions. They reveal useful insights into design of the tool motion
pattern with respect to the surface geometry. The simulation result of machining different surfaces validates the proposed
method. This work provides an effective systematic approach to precise error control in 5-axis flank milling.

0 Bookmarks
 · 
66 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: 5-axis machining technology has received much attention since the late 90's. It offers better machining efficiency and superior shaping capability compared with 3-axis machining. Machining error control is considered to be a challenging task in 5-axis flank milling of complex geometries. Previous studies have shown that optimized tool path planning is a feasible approach to reduction of the machining error. However, the error estimation is very time-consuming in the optimization process, thus limiting the practicality of the approach. In this work, we apply GPU computing technology to solve this problem. A PSO-based optimization scheme is developed to generate a series of cutter locations corresponding to a globally minimized machining error. The error induced by each cutter location is simultaneously calculated by the parallel processing units in GPU. This significantly accelerates the search process in the optimization scheme, while the optimal solution remains the same as that obtained by CPU. Our test result demonstrates the potential of improving the computational efficiency in CAD/CAM using GPU.
    01/2010;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Centrifugal impeller is a complex part commonly used in aerospace, energy, and air-conditioning industries. Its manufacture involves multi-axis free form machining, a time consuming and error-prone process. Tool path planning is considered a critical issue in the process but still lacking of systematic solutions. This paper proposes a tool path planning framework for 5-axis machining of centrifugal impeller with split blades. It provides several CAM functions that assist the users to generate collision-free cutter motions with smooth tool orientations. First, the machining process is divided into four operations and the planning tasks of each operation are standardized. Second, the hub surfaces are properly decomposed, re-grouped, and re-parameterized to facilitate calculation of quality tool path with reduced cutter retraction and plunging. Finally, geometric algorithms are developed to automatically detect tool collisions and then correct the erroneous tool orientations. An optimization scheme is applied to minimize the total amount of tool posture changes after the correction. An impeller is machined with the NC codes generated from the framework. The result shows the effectiveness of this work in automating the tool path planning in 5-axis machining of highly intricate impeller. KeywordsImpeller-5-Axis machining-Flank milling-Tool path planning-Tool collision
    Journal of Intelligent Manufacturing 01/2010; · 1.28 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This article proposes a novel planning method of multi-pass tool path in five-axis flank machining of ruled surfaces. The path planning task is first transformed into an optimal curve matching problem. The objective in the optimisation is represented as a weighted sum of the errors induced by overcut and undercut, respectively. Particle swarm optimisation algorithms are then applied to search for the optimal solutions and the corresponding tool paths. Running the algorithms multiple times generates a multi-pass tool path that progressively reduces machining errors. Different optimised results can be obtained for each pass by properly adjusting the weights in the objective. Numerical results indicate that the proposed method produces smaller machining errors compared to traditional planning of a single tool path. It offers a planning flexibility that has never been realised by previous studies.
    International Journal of Computer Integrated Manufacturing 01/2012; · 0.94 Impact Factor