512
Views
1
CrossRef citations to date
0
Altmetric
Original Articles

Vision-based surface roughness evaluation system for end milling

, &
Pages 727-738 | Received 20 Jan 2017, Accepted 13 Oct 2017, Published online: 24 Nov 2017

References

  • Al-Kindi, G. A., and B. Shirinzadeh. 2009. “Feasibility Assessment of Vision-Based Surface Roughness Parameters Acquisition for Different Types of Machined Specimens.” Image and Vision Computing 27 (4): 444–458. doi:10.1016/j.imavis.2008.06.011.
  • Baek, D. K., T. J. Ko, and H. S. Kim. 2001. “Optimization of Feedrate in a Face Milling Operation Using a Surface Roughness Model.” International Journal of Machine Tools and Manufacture 41: 451–462. doi:10.1016/S0890-6955(00)00039-0.
  • Chen, F. L., D. Joo, and J. T. Black. 1994. “Investigation of Cutting Condition Monitoring by Visual Measurement of Surface Texture Parameters.” International Journal of Computer Integrated Manufacturing 7 (5): 307–319. doi:10.1080/09511929408944618.
  • D’Addona, D. M., and R. Teti. 2013. “Image Data Processing via Neural Networks for Tool Wear Prediction.” Procedia CIRP 12: 252–257. doi:10.1016/j.procir.2013.09.044.
  • Datta, A., S. Dutta, S. K. Pal, and R. Sen. 2013. “Progressive Cutting Tool Wear Detection from Machined Surface Images Using Voronoi Tessellation Method.” Journal of Materials Processing Technology 213 (12): 2339–2349. doi:10.1016/j.jmatprotec.2013.07.008.
  • Davim, J. P. 2001. “A Note on the Determination of Optimal Cutting Conditions for Surface Finish Obtained in Turning Using Design of Experiments.” Journal of Materials Processing Technology 116: 305–308. doi:10.1016/S0924-0136(01)01063-9.
  • Dutta, S., S. K. Pal, S. Mukhopadhyay, and R. Sen. 2013. “Application of Digital Image Processing in Tool Condition Monitoring: A Review.” CIRP Journal of Manufacturing Science and Technology 6 (3): 212–232. doi:10.1016/j.cirpj.2013.02.005.
  • ISO 17450-1. 2011. Geometrical Product Specification (GPS) – General Concepts – Part 1: Model for Geometrical Specification and Verification. International Organization for Standardization, Geneva, Switzerland.
  • ISO 25178-2. 2012. Geometrical Product Specification (GPS) – Surface Texture: Areal – Part 2: Terms, Definitions and Surface Texture Parameters. International Organization for Standardization, Geneva, Switzerland.
  • Jiang, X., P. J. Scott, D. J. Whitehouse, and L. Blunt. 2007a. “Paradigm Shifts in Surface Metrology. Part I. Historical Philosophy.” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463 (2085): 2049–2070. doi:10.1098/rspa.2007.1874.
  • Jiang, X., P. J. Scott, D. J. Whitehouse, and L. Blunt. 2007b. “Paradigm Shifts in Surface Metrology. Part II. The Current Shift.” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 463 (2085): 2071–2099. doi:10.1098/rspa.2007.1873.
  • Jiang, X. J., and D. J. Whitehouse. 2012. “Technological Shifts in Surface Metrology.” CIRP Annals - Manufacturing Technology 61 (2): 815–836. doi:10.1016/j.cirp.2012.05.009.
  • Kumar, R. P., P. Kulashekar, B. Dhanasekar, and B. Ramamoorthy. 2005. “Application of Digital Image Magnification for Surface Roughness Evaluation Using Machine Vision.” International Journal of Machine Tools and Manufacture 45 (2): 228–234. doi:10.1016/j.ijmachtools.2004.07.001.
  • Lee, K. Y., M. C. Kang, Y. H. Jeong, D. W. Lee, and J. S. Kim. 2001. “Simulation of Surface Roughness and Profile in High-Speed End Milling.” Journal of Materials Processing Technology 113 (1–3): 410–415. doi:10.1016/S0924-0136(01)00697-5.
  • Marshall, A., and R. Martin. 1992. Computer Vision, Models, and Inspection, Series in Robotics and Automated Systems. Vol. 4. Cardiff: University of Wales.
  • Mezghani, S., and H. Zahouani. 2004. “Characterisation of the 3D Waviness and Roughness Motifs.” Wear 257 (12): 1250–1256. doi:10.1016/j.wear.2004.05.024.
  • Pernkopf, F., and P. O’Leary. 2003. “Image Acquisition Techniques for Automatic Visual Inspection of Metallic Surfaces.” NDT & E International 36 (8): 609–617. doi:10.1016/S0963-8695(03)00081-1.
  • Ryu, S. H., D. K. Choi, and C. N. Chu. 2006. “Roughness and Texture Generation on End Milled Surfaces.” International Journal of Machine Tools and Manufacture 46 (3–4): 404–412. doi:10.1016/j.ijmachtools.2005.05.010.
  • Samanta, B. 2009. “Surface Roughness Prediction in Machining Using Soft Computing.” International Journal of Computer Integrated Manufacturing 22 (3): 257–266. doi:10.1080/09511920802287138.
  • Stout, K. J. 1998. “Engineering Surfaces—A Philosophy of Manufacture (A Proposal for Good Manufacturing Practice).” Proceedings of the Institution of Mechanical Engineers, Part B, Journal of Engineering Manufacture 212 (3): 169–174. doi:10.1243/0954405981515581.
  • Thomas, T. R. 1999. Rough Surfaces. 2nd ed. London: Imperial College Press.
  • Venkat Ramana, K., and B. Ramamoorthy. 1996. “Statistical Methods to Compare the Texture Features of Machined Surfaces.” Pattern Recognition 29 (9): 1447–1459. doi:10.1016/0031-3203(96)00008-8.
  • Wang, M.-Y., and H.-Y. Chang. 2004. “Experimental Study of Surface Roughness in Slot End Milling AL2014-T6.” International Journal of Machine Tools and Manufacture 44 (1): 51–57. doi:10.1016/j.ijmachtools.2003.08.011.
  • Whitehouse, D. J. 1994. Handbook of Surface Metrology. Bristol and Philadelphia: Institute of Physics Publishing.
  • Zhang, X.-W., D. Yan-Qiong, L. Yan-Yun, S. Ai-Ye, and L. Rui-Yu. 2011. “A Vision Inspection System for the Surface Defects of Strongly Reflected Metal Based on Multi-Class SVM.” Expert Systems with Applications 38 (5): 5930–5939. doi:10.1016/j.eswa.2010.11.030.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.