Proposal of a recognition method of machining features in computer aided process planning system for complex parts machining
Proposal of a recognition method of machining features in computer aided process planning system for complex parts machining
复制标题
复杂零件加工计算机辅助工艺规划系统中加工特征识别方法的提出
DOI：
10.1299/transjsme.16-00574
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
K. Nakamoto
中科院分区：
文献类型：
--
作者：
Yuki Inoue;K. Nakamoto
近年来，制造业趋向多品种、小批量生产。因此，在机械加工领域，准备工作在前置时间内的比例变得更高，因为准备工作需要花费大量的时间和精力来决定合适的加工方法、分配目标零件、选择刀具和生成刀具路径。因此，迫切需要开发一种计算机辅助工艺规划（CAPP）系统来缩短准备时间并生成数控程序。特征识别被认为是开发CAPP系统的关键技术，长期以来已有大量研究人员致力于该技术的研究。在作者之前的研究中，已经提出了多任务机床的新颖加工功能。加工特征可以对应于多种替代加工方法。然而，尚未考虑实际机械零件的复杂目标形状。为了解决这个问题，首先对倒角部分、自由曲面等特殊形状进行近似，并通过简化复杂凹槽或锥体形状等加工基元来识别加工特征。本研究中的加工基元最终被恢复为CAM系统原始的复杂形状。从案例研究的结果来看，人们认识到所提出的特征识别方法具有处理实际机械零件的复杂目标形状的潜力。
Manufacturing industry tends toward high-mix low-volume production in recent years. Therefore, in the field of machining, the ratio of preparation in the lead-time becomes higher because the preparation takes a great deal of time and labor to decide suitable machining method, allocate target parts, select cutting tools and generate tool paths. As a result, it is strongly required to develop a computer aided process planning (CAPP) system to shorten the preparation time and to generate NC program. Feature recognition has been considered as a key technology to develop a CAPP system, and a lot of researches have been tackling the technology for a long time. In authors’ previous study, novel machining features for multi-tasking machine tools have been proposed. The machining features can correspond to several alternative machining methods. However, complex target shapes of practical mechanical parts have not been considered. In order to solve this problem, special shapes such as chamfer part and freeform surface are firstly approximated and machining features are recognized by simplifying machining primitives such as complicated groove or taper shape. The machining primitives are finally restored to original complex shapes for CAM system in this study. From the results of conducted case study, it is recognized that the proposed feature recognition method has a potential to deal with complex target shapes of practical mechanical parts.