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A Generic Multi-Axis Post-Processor Engine for Optimal CNC Data Creation and Intelligent Surface Machining

机译:用于优化CNC数据创建和智能表面加工的通用多轴后处理器引擎

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摘要

This paper focuses on the development of a multi-axis post-processor engine with a curvature-based feed adaptation module, capable of extracting generic CNC data for high precision machining. The motivation of this work stems from the drawback of standard and commercial post-processors to modify their internal source codes so as to be implemented to newly-developed functions which integrate modern CNC units. The multi-axis post-processor proposed in this work operates as a stand-alone function of an artificial intelligent module that optimizes machining parameters for standard swept cut multi-axis surface tool-paths. The post-processor developed receives APT source files previously been optimized by means of a genetic algorithm that handles cutting tool selection; radial cut engagement; maximum discretization step; lead and tilt angles. The algorithm optimizes the aforementioned machining parameters towards the minimization of the number of cutter locations found in a specific APT source file as well as the surface machining error as a combined effect of chordal deviation and scallop height. The final APT output is then properly handled by the post-processor engine so as to extract the final ISO code for a double-pivoted head 5-axis CNC machine and compute optimal values for feed rate in each NC block considering the interpolation error and curvature analysis given the surface properties. To simulate and verify our proposals, the MAZAK Vortex 1000 gantry-type 5-axis CNC machine tool equipped with a Fanuc 15i CNC unit has been selected as the manufacturing resource corresponding to the final CNC output that the proposed post-processor computes. A benchmark sculptured part is created and used for the virtual material removal simulation in CATIA~® V5 R18. For that part, both the proposed post-processor engine and a commercially available post-processor were employed to extract G-code data whilst it was shown that identical outputs were obtained.Post-processor, CNC machining, cutter location data, intelligent tool-paths.
机译:本文着重于开发具有基于曲率的进给适配模块的多轴后处理器引擎,该引擎能够提取通用的CNC数据以进行高精度加工。这项工作的动机源于标准和商业后处理器修改其内部源代码,以便将其实现为集成了现代CNC单元的新开发功能的缺点。在这项工作中提出的多轴后处理器可以作为人工智能模块的独立功能运行,该模块可以优化标准扫掠多轴曲面刀具路径的加工参数。开发的后处理器接收先前通过处理切割工具选择的遗传算法进行优化的APT源文件。径向切入最大离散化步骤;超前角和倾斜角。该算法优化了上述加工参数,以使在特定APT源文件中找到的刀具位置数量以及表面加工误差(弦和弦和扇贝高度的综合影响)最小化。然后,由后期处理器引擎正确处理最终的APT输出,以便为双回转头5轴CNC机床提取最终的ISO代码,并考虑插值误差和曲率,计算每个NC块中的进给率的最佳值分析给出的表面性质。为了模拟和验证我们的建议,已选择配备有Fanuc 15i CNC单元的MAZAK Vortex 1000龙门式5轴CNC机床作为制造资源,与建议的后处理器计算出的最终CNC输出相对应。创建了基准雕刻零件,并将其用于CATIA〜®V5 R18中的虚拟材料去除模拟。对于那部分,建议的后处理器引擎和市售的后处理器都被用来提取G代码数据,同时显示出获得了相同的输出。后处理器,CNC加工,刀具位置数据,智能刀具-路径。

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  • 来源
    《Precision machining IX》|2017年|463-469|共7页
  • 会议地点 Athens(GR)
  • 作者单位

    Laboratory of Manufacturing Processes and Machine Tools (LMProMaT), Department of Mechanical Engineering Educators, School of Pedagogical and Technological Education (ASPETE), GR 14121, N. Heraklion Attikis, Athens, Greece;

    Department of Mechanical Engineering, Piraeus University of Applied Sciences, GR 12244, Egaleo, Athens, Greece;

    Laboratory of Manufacturing Processes and Machine Tools (LMProMaT), Department of Mechanical Engineering Educators, School of Pedagogical and Technological Education (ASPETE), GR 14121, N. Heraklion Attikis, Athens, Greece;

    Faculty of Science, Engineering and Computing (SEC), Roehampton Vale Campus, Kingston University, Friars Avenue, Kingston Upon Thames, SW15 3DW London, UK;

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  • 正文语种 eng
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