Industrial & Manufacturing

MACHINE VISION

Research in the area of machine vision includes the application of machine vision in tool wear studies, in-cycle assessment of tool wear and surface roughness, non-contact measurement of surface roughness, non-destructive testing (weld radiography), dimensional measurement, inspection and measurement using the flatbed scanner as well as image processing. Some of the recent publications in this field are:

  1. H.H. Shahabi, M.M. Ratnam, Non-contact roughness measurement of turned parts using machine vision, International Journal of Advanced Manufacturing Technology 46: 275-284(2010).
  2. H.H. Shahabi, M.M. Ratnam, In-cycle detection of built-up edge (BUE) from 2-D images of cutting tools using machine vision, International Journal of Advanced Manufacturing Technology 46: 1178-1189 (2010).
  3. H.H. Shahabi, M.M. Ratnam, Prediction of surface roughness and dimensional deviation of workpiece in turning: A machine vision approach, International Journal of Advanced Manufacturing Technology 48: 213-226 (2010).
  4. G.J. Chian, M.M. Ratnam, Determination of tool nose radii of cutting inserts using machine vision, Sensor Review 31(2) (2010-accepted).
  5. S. J. Abdullah, M. M. Ratnam, Z. Samad, Error-based autofocus system using image feedback in liquid-filled diaphragm lens, Optical Engineering 48(12) (2009).
  6. H.H. Shahabi, M.M Ratnam, Study on the effect of nose wear and groove wear on surface roughness of turned parts using machine vision, World Applied Sciences Journal 7(3): 343-349 (2009)
  7. C.W. Kee, M.M. Ratnam, A simple approach to fine wire diameter measurement using high-resolution flatbed scanner, International Journal of Advanced Manufacturing Technology 40: 940-947 (2009).
  8. H.H. Shahabi, M. M. Ratnam, In-cycle monitoring of tool nose wear and surface roughness of turned parts using machine vision, International Journal of Advanced Manufacturing Technology 40: 1148-1157 (2009).
  9. H.H. Shahabi, M. M. Ratnam, Assessment of flank wear and nose radius wear from workpiece roughness profile in turning operation using machine vision, International Journal of Advanced Manufacturing Technology 43(1-2): 11-21 (2009).
  10. T.Y.Lim, M.M.Ratnam, M.A.Khalid, Automatic weld bead extraction from digitised radiographs using grey level intensity profiles and least-squares fitting, Insight - Non-Destructive Testing & Condition Monitoring (the Journal of British Institute of Non-Destructive Testing), 50(1):1-6 (2008).
  11. S.L Soo, Ratnam M.M., Samad Z., M. A. Khalid, Segmentation of weld defects in radiographs using rank-leveling and background subtraction, Insight - Non-Destructive Testing & Condition Monitoring (the  Journal of British Institute of Non-Destructive Testing) 50(4): 188-194 (2008).
  12. H.H.Shahabi, M.M.Ratnam, On-line monitoring of tool wear in turning operation in the presence of tool misalignment, International Journal of Advanced Manufacturing Technology, 38(7-8): 718-727 (2008).

For more information please contact: Professor Mani Maran Ratnam

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