Dynamic machining process planning incorporating in-process workpiece deformation data for large-size aircraft structural parts

References

• Aliyev, R. 2006. “A Strategy for Selection of the Optimal Machining Sequence in High Speed Milling Process.” International Journal of Computer Applications in Technology 27 (1): 72–82. doi:10.1504/IJCAT.2006.010990.
   Google Scholar
• Bort, C. M. G., M. Leonesio, and P. Bosetti. 2016. “A Model-Based Adaptive Controller for Chatter Mitigation and Productivity Enhancement in CNC Milling Machines.” Robotics & Computer Integrated Manufacturing 40: 34–43. doi:10.1016/j.rcim.2016.01.006.
   Web of Science ®Google Scholar
• Bowden DM, H. J. 2001. Aluminium reliability improvement program-final report 60606. Boeing Company: Chicago.
   Google Scholar
• Bzymek, Z. M., M. Nunez, M. Li, and S. Powers. 2008. “Simulation of a Machining Sequence Using Delmia/Quest Software.” Computer-Aided Design & Applications 5 (1–4): 401–411. doi:10.3722/cadaps.2008.401-411.
   Google Scholar
• Cerutti, X., and K. Mocellin. 2016. “Influence of the Machining Sequence on the Residual Stress Redistribution and Machining Quality: Analysis and Improvement Using Numerical Simulations.” International Journal of Advanced Manufacturing Technology 83 (1–4): 489–503. doi:10.1007/s00170-015-7521-4.
   Web of Science ®Google Scholar
• Chantzis, D., S. Van-der-Veen, J. Zettler, and W. M. Sim 2013. An Industrial Workflow to Minimise Part Distortion for Machining of Large Monolithic Components in Aerospace Industry. 14th CIRP Conference on Modeling Of Machining Operations (CIRP CMMO), 8, 281–286, Torino, June 13-14.
   Google Scholar
• Diez, E., H. Perez, J. Marquez, and A. Vizan. 2015. “Feasibility Study of In-Process Compensation of Deformations in Flexible Milling.” International Journal of Machine Tools & Manufacture 94: 1–14. doi:10.1016/j.ijmachtools.2015.03.008.
   Web of Science ®Google Scholar
• Djurdjanovic, D., L. Mears, F. A. Niaki, A. U. Haq, and L. Li. 2018. “State of the Art in Process, System and Operation Level Control in Modern Manufacturing.” Journal of Manufacturing Science & Engineering 140 (6): 061010. doi:10.1115/1.4038074.
   Web of Science ®Google Scholar
• Dong H Y, Y.-L. K. E. 2006. “Study on Machining Deformation of Aircraft Monolithic Component by FEM and Experiment.” Chinese Journal of Aeronautics 19 (3): 247–254. doi:10.1016/S1000-9361(11)60352-X.
   Google Scholar
• Guo, H., D. W. Zuo, S. H. Wang, X. U. Li-Lin, and W. Min. 2005. “Effect of Tool-Path on Milling Accuracy under Clamping.” Transactions of Nanjing University of Aeronautics and Astronautics 22: 234–239.
   Google Scholar
• Heo, E. Y., D. W. Kim, J. Y. Lee, C. S. Lee, and F. F. Chen. 2011. “High Speed Pocket Milling Planning by Feature-Based Machining Area Partitioning.” Robotics and Computer-Integrated Manufacturing 27 (4): 706–713. doi:10.1016/j.rcim.2010.12.007.
   Web of Science ®Google Scholar
• Huang, W., Y. Hu, and L. Cai. 2012. “An Effective Hybrid Graph and Genetic Algorithm Approach to Process Planning Optimization for Prismatic Parts.” International Journal of Advanced Manufacturing Technology 62 (9–12): 1219–1232. doi:10.1007/s00170-011-3870-9.
   Web of Science ®Google Scholar
• Huang, X. M., J. Sun, and J. F. Li. 2015. “Finite Element Simulation and Experimental Investigation on the Residual Stress-Related Monolithic Component Deformation.” International Journal of Advanced Manufacturing Technology 77 (5–8): 1035–1041. doi:10.1007/s00170-014-6533-9.
   Web of Science ®Google Scholar
• Huang, Z. G., K. E. Ying-Lin, and H. Y. Dong. 2005. “Finite Element Model of Milling Process Sequence Forframe Monolithic Components.” Journal of Zhejiang University 03:54–58. In Chinese.
   Google Scholar
• Jiang, X. 2014. Investigation on the Mechanism of the Residual Stress and Control Method of Machining Accuracy for the Complex Thin-Walled Parts. PhD Diss., Donghua University.
   Google Scholar
• Keleshian, N., R. Kyser, J. Rodriguez, C. Cueva, V. Vega, E. W. Lee, J. Ogren, and O. S. Es-Said. 2011. “On the Distortion and Warpage of 7249 Aluminum Alloy after Quenching and Machining.” Journal of Materials Engineering & Performance 20 (7): 1230–1234. doi:10.1007/s11665-010-9756-4.
   Web of Science ®Google Scholar
• Kumar, C., and S. Deb. 2012. “Generation of Optimal Sequence of Machining Operations in Setup Planning by Genetic Algorithms.” Journal of Advanced Manufacturing Systems 11 (01): 67–80. doi:10.1142/S0219686712500059.
   Google Scholar
• Li, B., X. Y. Zuo, J. Yang, X. Jiang, and J. Ni. 2014. “Interactive Influence of Linked Characteristics during Machining of Thin-Walled Parts.” International Journal of Advanced Manufacturing Technology 72 (9–12): 1727–1734. doi:10.1007/s00170-014-5797-4.
   Web of Science ®Google Scholar
• Li, J. G., and S. Q. Wang. 2017. “Distortion Caused by Residual Stresses in Machining Aeronautical Aluminum Alloy Parts: Recent Advances.” International Journal of Advanced Manufacturing Technology 89 (1–4): 997–1012. doi:10.1007/s00170-016-9066-6.
   Web of Science ®Google Scholar
• Li, Y., C. Liu, X. Hao, J. X. Gao, and P. G. Maropoulos. 2015. “Responsive Fixture Design Using Dynamic Product Inspection and Monitoring Technologies for the Precision Machining of Large-Scale Aerospace Parts.” CIRP Annals - Manufacturing Technology 64 (1): 173–176. doi:10.1016/j.cirp.2015.04.025.
   Web of Science ®Google Scholar
• Li, Y. G., Y. F. Ding, W. P. Mou, and H. Guo. 2010. “Feature Recognition Technology for Aircraft Structural Parts Based on a Holistic Attribute Adjacency Graph.” Proceedings of the Institution of Mechanical Engineers Part B: Journal of Engineering Manufacture 224 (2): 271–278. doi:10.1243/09544054JEM1634.
   Web of Science ®Google Scholar
• Lin, A. C., S. Y. Lin, D. Diganta, and W. F. Lu. 1998. “An Integrated Approach to Determining the Sequence of Machining Operations for Prismatic Parts with Interacting Features.” Journal of Materials Processing Technology 73 (1–3): 234–250. doi:10.1016/S0924-0136(97)00233-1.
   Web of Science ®Google Scholar
• Liu, C., Y. Li, and W. Shen. 2014. “Integrated Manufacturing Process Planning and Control Based on Intelligent Agents and Multi-Dimension Features.” International Journal of Advanced Manufacturing Technology 75 (9–12): 1457–1471. doi:10.1007/s00170-014-6246-0.
   Web of Science ®Google Scholar
• Liu, Z., and L. Wang. 2007. “Sequencing of Interacting Prismatic Machining Features for Process Planning.” Computers in Industry 58 (4): 295–303. doi:10.1016/j.compind.2006.07.003.
   Web of Science ®Google Scholar
• Qiao, L., X. Y. Wang, and S. C. Wang. 2000. “A GA-based Approach to Machining Operation Sequencing for Prismatic Parts.” International Journal of Production Research 38 (14): 3283–3303. doi:10.1080/002075400418261.
   Web of Science ®Google Scholar
• Qiao, L. H., Q. W. Hu, and H. W. Zhang. 2012. “Machining Sequencing Optimization Based on Simulated Annealing Algorithm.” Advanced Materials Research 472-475: 1632–1636. doi:10.4028/www.scientific.net/AMR.472-475.
   Google Scholar
• Rai, J. K., and P. Xirouchakis. 2008. “Finite Element Method Based Machining Simulation Environment for Analyzing Part Errors Induced during Milling of Thin-Walled Components.” International Journal of Machine Tools & Manufacture 48 (6): 629–643. doi:10.1016/j.ijmachtools.2007.11.004.
   Web of Science ®Google Scholar
• Ramesh, R., M. A. Mannan, and A. N. Poo. 2000. “Error Compensation in Machine Tools - a Review Part I: Geometric, Cutting-Force Induced and Fixture-Dependent Errors.” International Journal of Machine Tools & Manufacture 40 (9): 1235–1256. doi:10.1016/S0890-6955(00)00009-2.
   Web of Science ®Google Scholar
• Richter-Trummer, V., D. Koch, A. Witte, J. F. Dos Santos, and P. M. S. T. de Castro. 2013. “Methodology for Prediction of Distortion of Workpieces Manufactured by High Speed Machining Based on an Accurate Through-The-Thickness Residual Stress Determination.” International Journal of Advanced Manufacturing Technology 68 (9–12): 2271–2281. doi:10.1007/s00170-013-4828-x.
   Web of Science ®Google Scholar
• Singh, S., and S. Deb. 2014. “An Intelligent Methodology for Optimizing Machining Operation Sequence by Ant System Algorithm.” International Journal of Industrial & Systems Engineering 16 (4): 451–471. doi:10.1504/IJISE.2014.060654.
   Google Scholar
• Suh, S. H., J. H. Cho, and J. Y. Hascoet. 1996. “Incorporation of Tool Deflection in Tool Path Computation: Simulation and Analysis.” Journal of Manufacturing Systems 15 (3): 190–199. doi:10.1016/0278-6125(96)89571-9.
   Web of Science ®Google Scholar
• Tang, Z. T., Z. Q. Liu, and L. Q. Xu. 2010. “Effect of Process Routing on Machining Deformation for Multi-Frame Double Sided Monolithic Components.” Advanced Materials Research 97-101: 2894–2897. doi:10.4028/www.scientific.net/AMR.97-101.
   Google Scholar
• Wang, L., N. Cai, and H. Y. Feng. 2004. “Generic Machining Sequence Generation Using Enriched Machining Features.” Transactions of the North American Manufacturing Research Institute of SME 32: 55–62.
   Google Scholar
• Wang, L., N. Cai, H.-Y. Feng, and Z. Liu. 2006. “Enriched Machining Feature-Based Reasoning for Generic Machining Process Sequencing.” International Journal of Production Research 44 (8): 1479–1501. doi:10.1080/00207540500354119.
   Web of Science ®Google Scholar
• Woo, Y., and S. Kang. 2016. “Automatic Generation of Machining Sequence for Machined Parts Using Machining Features.” Journal of the Korea Academia-Industrial Cooperation Society 17 (2): 642–648. doi:10.5762/KAIS.2016.17.2.642.
   Google Scholar
• Wu, Y. G., S. M. Gao, and Z. C. Chen. 2001. “An Approach to Establish Machining Sequence for Intersecting Features.” Journal of Computer Aided Design & Computer Graphics 13(10): 937–942 .
   Google Scholar
• Xu, X., L. Wang, and S. T. Newman. 2011. “Computer-Aided Process Planning – A Critical Review of Recent Developments and Future Trends.” International Journal of Computer Integrated Manufacturing 24 (1): 1–31. doi:10.1080/0951192X.2010.518632.
   Web of Science ®Google Scholar
• Zhang, G. M., C. Yu, R. C. Shi, and L. B. An. 2003. “Experimental Study on the Milling of Thin Parts of Titanium Alloy (TC4).” Journal of Materials Processing Technology 138 (1–3): 489–493. doi:10.1016/S0924-0136(03)00126-2.
   Web of Science ®Google Scholar
• Zhang, X., A. Nassehi, and S. T. Newman. 2015. “A Meta-Model of Computer Numerical Controlled Part Programming Languages.” Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture 229 (7): 1243–1257. doi:10.1177/0954405415585084.
   Web of Science ®Google Scholar