Machine Tool Assignment Realized by Automated NC Program Generation and Machining Time Prediction
Isamu Nishida and Keiichi Shirase
1-1 Rokko-dai, Nada-ku, Kobe, Hyogo 657-8501, Japan
The present study proposed a method to automatically generate a numerical control (NC) program by referring to machining case data for each machine tool with only 3D-CAD models of a product and workpiece as the input data, and to select machine tools for machining the target removal region among several machine tools with different characteristics. The special features of the proposed method are described as follows. The removal volume can be automatically obtained from the total removal volume (TRV), which is extracted from the workpiece and product using a Boolean operation by dividing it on the XY plane. The removal region changed according to the determined machining sequence. The conditions for machining the removal region is automatically determined according to the machining case data, which is stored by linking the geometric properties of the removal region with the machining conditions determined by experienced operators. Furthermore, an NC program is automatically generated based on the machining conditions. The machine tools for machining the target region are selected according to the predicted machining time of each machine tool connected by a network.
A case study was conducted to validate the effectiveness of the proposed system. The results confirm that machining can be conducted using only 3D-CAD models as input data. It was suggested that the makespan would be shortened by changing the machining sequence from the optimized machining sequence when machining a plurality of products.
-  N. Sugimura, “Research trends in process planning,” J. of the Japan Society for Precision Engineering, Vol.72, No.2, pp. 165-170, 2006 (in Japanese).
-  D. Hamada, K. Nakamoto, T. Ishida, and Y. Takeuchi, “Development of CAPP system for multi-tasking machine tool,” Trans. of the Japan Society of Mechanical Engineers, Series C, Vol.78, No.791, pp. 2698-2709, 2012 (in Japanese).
-  L. Wang, M. Holm, and G. Adamson, “Embedding a process plan in function blocks for adaptive machining,” CIRP Annals-Manufacturing Technology, Vol.59, Issue 1, pp. 433-436, 2010.
-  Y. Woo, E. Wang, Y. S. Kim, and H. M. Rho, “A hybrid feature recognizer for machining process planning systems,” CIRP Annals-Manufacturing Technology, Vol.54, Issue 1, pp. 397-400, 2005.
-  M. El-Mehalawi and R.A. Miller, “A database system of mechanical components based on geometric and topological similarity. Part I: representation,” Computer-Aided Design, Vol.35, No.1, pp. 83-94, 2003.
-  M. El-Mehalawi and R. A. Miller, “A database system of mechanical components based on geometric and topological similarity. Part II: indexing, retrieval, matching and similarity assessment,” Computer-Aided Design, Vol.35, No.1, pp. 95-105, 2003.
-  K. Nakamoto, K. Shirase, H. Wakamatsu, A. Tsumaya, and E. Arai, “Automatic production planning system to achieve flexible direct machining,” JSME Int. J. Series C, Vol.47, No.1, pp. 136-143, 2004.
-  A. Ueno and K. Nakamoto, “Proposal of machining features for CAPP system for multi-tasking machine tools,” Trans. of the JSME, Vol.81, No.825, p. 15-00108, doi: 10.1299/transjsme.15-00108, 2015 (in Japanese).
-  E. Morinaga, M. Yamada, H. Wakamatsu, and E. Arai, “Flexible process planning method for milling,” Int. J. Automation Technol., Vol.5, No.5, pp. 700-707, 2011.
-  E. Morinaga, T. Hara, H. Joko, H. Wakamatsu, and E. Arai, “Improvement of computational efficiency in flexible computer-aided process planning,” Int. J. Automation Technol., Vol.8, No.3, pp. 396-405, 2014.
-  K. Dwijayanti and H. Aoyama, “Basic study on process planning for turning-milling center based on machining feature recognition,” J. of Advanced Mechanical Design, Systems and Manufacturing, Vol.8, No.4, JAMDSM0058, 2014.
-  H. Sakurai and P. Dave, “Volume decomposition and feature recognition, part I – polyhedral objects,” Computer-Aided Design, Vol.27, Issue 11, pp. 793-869, 1995.
-  H. Sakurai, and P. Dave, “Volume decomposition and feature recognition, part II – curved objects,” Computer-Aided Design, Vol.28, Issues 6-7, pp. 519-537, 1996.
-  T. Inoue and K. Nakamoto, “Proposal of a recognition method of machining features in computer aided process planning system for complex parts machining,” Trans. of the JSME, Vol.83, No.850, p. 16-00574, doi: 10.1299/transjsme.16-00574, 2017 (in Japanese).
-  M. M. Isnaini, Y. Shinoki, R. Sato, and K. Shirase, “Development of a CAD-CAM interaction system to generate a flexible machining process plan,” Int. J. Automation Technol., Vol.9, No.2, pp. 104-114, 2015.
-  I. Nishida, R. Sato, and K. Shirase, “Proposal of process planning system for end-milling operation considering product design constraints,” Trans. of the Institute of Systems, Control and Information Engineers, Vol.30, pp. 81-86, 2017 (in Japanese).
-  I. Nishida, T. Hirai, R. Sato, and K. Shirase, “Automatic process planning system for end-milling operation considering CAM operator’s intention,” Trans. of the JSME, Vol.84, No.860, pp. 81-86, doi: 10.1299/transjsme.17-00563, 2018 (in Japanese).
-  I. Nishida and K. Shirase, “Automated process planning system for end-milling operation considering constraints of operation (1st report Process planning to minimize the number of times of tool change),” Trans. of the JSME, Vol.84, No.866, doi: 10.1299/transjsme.18-00242, 2018 (in Japanese).
-  T. Inoue, T. Kishinami, and F. Tanaka, “Study of process planning based on feature dependency of manufacturing features (1st Report: The representation of feature dependency and basic concept of process planning system),” J. of the Japan Society for Precision Engineering, Vol.73, No.4, pp. 487-491, 2007 (in Japanese).
-  I. Nishida and K. Shirase, “Automatic determination of cutting conditions for NC program generation by reusing machining case data based on geometric properties of removal volume,” J. of Advanced Mechanical Design, Systems, and Manufacturing, Vol.12, No.4, JAMDSM0093, doi: 10.1299/jamdsm.2018jamdsm0093055, 2018.