Part localization theory and its application on near-net-shape machining
- 6 Downloads
As an emerging technique, near-net-shape machining implies that billets of a part are near to its net shape (or its design), and thus, little machining of the billets is required to produce qualified pieces. This technique has been employed in production of critical parts, repair of important but worn out parts, and machining of three-dimensional (3-D) printed parts. To cut a near-net-shape billet, its part localization should be conducted by transforming (or localizing) its part design model geometrically such that the transformed model is inside the billet and within the part tolerances. This transformed model is called machining model. After that, the machining model is used to generate tool paths and the billet is cut with the tool along the paths. Unfortunately, the current problem of this technique is that the conventional part localization methods cannot ensure that the transformed model is within the tolerance and tool paths generated with this model cannot be used to cut the billet for a qualified piece. To address this problem, an innovative and practical approach is proposed to transform part features individually, making sure that the transformed model is inside the billet model and satisfies the part tolerance. In this work, three practical examples are rendered to verify this approach. This approach lays a theoretical foundation of part localization and is an effective solution to near-net-shape machining in industry.
KeywordsMachining model Near-net-shape machining Part localization Worn parts repair Additive machining
Unable to display preview. Download preview PDF.
The financial support of this work was provided by the National Natural Science Foundations of China (51475381 and 51775445) and the Aeronautical Science Foundation of China (Grant No. 2017ZE53053).
- 1.Li X.M., Yeung M., and Li Z.X., 1996, An algebraic algorithm for workpiece localization. Proceedings of the IEEE International Conference on Robotics and Automation, pp. 152–158Google Scholar
- 4.Chu Y.X., Gou J.B., and Li Z.X., 1998, On the hybrid workpiece localization/envelopment problems, Proceedings of the 1998 IEEE International Conference on Robotics & Automation, 4, pp. 3665–3670Google Scholar
- 11.Yan SJ, Zhou YF, Peng FY, Lai XD (2004) Research on the localization of the workpieces with large sculptured surfaces in NC machining. Int J Adv Manuf Technol 23(5–6):429–435Google Scholar
- 12.Sun YW, Wang XM, Guo DM (2009) Machining localization and quality evaluation of parts with sculptured surfaces using SQP method. Int J Adv Manuf Technol 42(11–12):1131–1139Google Scholar
- 15.Han C., Zhang D.H., Wu B.H., Pu K., and Luo M., 2014, Localization of freeform surface workpiece with particle swarm optimization algorithm, 2014 international conference on innovative design and manufacturing, pp. 47–52Google Scholar
- 16.Zhang Y, Zhang DH, Wu BH (2015) An approach for machining allowance optimization of complex parts with integrated structure. J Comput Des Eng 2(4):248–252Google Scholar
- 17.Zhang Y, Zhang DH, Wu BH (2015) An adaptive approach to error compensation by on-machine measurement for precision machining of thin-walled blade, 2015 IEEE international on advanced intelligent. Mechatronics:1356–1360Google Scholar
- 18.Zhang Y, Chen ZT, Ning T (2015) Efficient measurement of aero-engine blade considering uncertainties in adaptive machining. Int J Adv Manuf Technol:1–10Google Scholar
- 19.Wu BH, Wang J, Zhang Y, Luo M (2015) Adaptive location of repaired blade for multi-axis milling. J Comput Des Eng 2(4):261–267Google Scholar
- 20.Chu Y.X., Gou J.B., Kang B., Woo K.T., and Li Z.X., 1997, Performance analysis of localization algorithms. Proceedings of the 1997 IEEE International Conference on Robotics and Automation, 2, pp. 1247–1252Google Scholar
- 21.Chu Y.X., Gou J.B., Wu H., and Li Z.X., 1998, Localization algorithms: performance evaluation and reliability analysis. Proceedings of the 1998 IEEE International Conference on Robotics and Automation, 4, pp. 3652–3657Google Scholar
- 27.Li W.L., Yin Z.P., and Xiong Y.L., 2009, Adaptive distance function and its application in free-form surface localization. Proceedings of the 2009 IEEE International Conference on Information and Automation, pp. 24–28Google Scholar
- 31.Xiong Z.H., Wang M.Y., and Li Z.X., 2003, A computer-aided probing strategy for workpiece localization. Proceedings of the 2003 IEEE International Conference on Robotics and Automation, 3, pp. 3941–3946Google Scholar
- 34.Zhu L.M., Luo H.G., and Ding H., 2004, Optimal measurement point planning for workpiece localization. Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2, pp. 1562–1567Google Scholar