基于计算机辅助制造系统实验设计的“按区域粗加工”的刀具路径策略决策

G. Vosniakos, Asimina Gkortza, N. Kontolatis
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引用次数: 2

摘要

这项工作简化了计算机辅助制造(CAM)系统中复杂零件的粗加工策略分配。以Pelton水轮机铲斗为例,将其划分为独立的区域。对于每个区域,适用的策略,工具路径类型,以及它们各自的参数都在足够小的离散级别上进行检查,以确保实际的可行性。响应,即加工时间和休息材料,被组合成一个单一的加权函数。田口设计保证了可能情况的绝对最小数量,并确定了最佳因子水平。方差分析揭示了每个因素的重要性,但也可能遗漏因素和/或可能发生的相互作用。该方法节省了时间,可以通过简单地添加缺失的实验来进行修正,并且同样适用于任何要加工的机械部件。[2015年9月30日收到;2016年2月17日修订;接受2016年2月23日]
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toolpath strategy decisions in 'rough machining-by-region' using design of experiments on computer-aided manufacturing systems
This work streamlines assignment of roughing strategies for complex parts from those that are available on a computer-aided manufacturing (CAM) system. A Pelton hydro-turbine bucket is used as an example, divided into independent regions. For each region the applicable strategies, toolpath types, as well as their individual parameters are examined at a small enough number of discrete levels to ensure practical feasibility. The responses, i.e. machining time and rest material, are combined into a single weighting function. The absolute minimum number of possible scenarios is guaranteed by Taguchi design and the optimum factor levels are determined. Analysis of variance reveals the significance of each factor but also possible omissions of factors and/or interactions that may occur. The approach saves time, is open to rectification by simply adding the missing experiments and is equally applicable to any mechanical component to be machined. [Received 30 September 2015; Revised 17 February 2016; Accepted 23 February 2016]
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