Process planning for die and mold machining based on pattern recognition and deep learning

Dies and molds are necessary elements in the manufacturing of current industrial products. There is increasing pressure to machine high quality complicated surfaces at low cost. The standardization process planning said be a key improving efficiency machining operations practice. Thus, computer aided (CAPP) systems urgently needed reduce time effort preparing operations. However, it difficult generalize that continues depend on skillful experts requires long preparation for die mold machining. On other hand, overcome issues generalize, well known learning has capability estimate valid values according past case data. Therefore, this study aims develop CAPP system can determine information based pattern recognition deep learning, kind learning. A network architecture called 3D u-net adapted effectively analyze whole images by producing segmented regions. Using voxel model representing targeted shape, becomes easier deal with generally three-dimensionally, as skilled pay attention geometrical features. Cutting tool type path treated determined system. results studies confirm developed effective determining even implicit know-how.