著者

高橋 辰伍 板野 健太郎 中本 圭一

出版者

一般社団法人 日本機械学会

雑誌

日本機械学会論文集 (ISSN:21879761)

巻号頁・発行日

vol.83, no.856, pp.17-00249-17-00249, 2017 (Released:2017-12-25)

参考文献数

13

被引用文献数

1

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Agile manufacturing that can rapidly machine advanced materials or creative shapes is expected as an important key to realize mass customization of industrial products. Most of high-value-added workpieces have three dimensional and complex shapes. Thus, the workpiece shape and stiffness vary greatly according to cutting procedure during a rough machining operation. The induced displacement of workpiece strongly affects machining accuracy and tool life. However, it is difficult to automatically determine the process planning in commercial CAM system because of a large number of combinations. Therefore, the process planning has been designed by skillful experts to achieve complex parts machining. In order to realize future high efficient machining, it is necessary to obtain these tacit knowledges and to formulate the implicit machining know-how owned by skillful experts. As the first step, a method is proposed to decide workpiece shapes during a rough machining operation to ensure the workpiece stiffness based on topology optimization in this study. Topology optimization that is known as one of the highly flexible structure optimization methods enables to deal with the target configuration and shape. By introducing changeable fixed design domain and discretized characteristic function, an optimization problem can be converted to a problem of material distribution. In this study, the topology optimization is applied to decide workpiece shapes during a rough machining operation. As a purpose of minimizing their mean compliance, the optimized workpiece shape is calculated depending on applied loads at each machining step. By using the calculated workpiece shapes, a case study of complex parts machining is conducted. From the result, it is confirmed that a rough machining operation of complex parts can be achieved according to the decided workpiece shapes.