ENG  Vol.8 No.5 , May 2016
Topography Measurement for Monitoring Manufacturing Processes in Harsh Conditions
Abstract: High precision manufacturing, e.g. milling and grinding, which have manufacturing tolerances in the range of <10 μm require microscopic measurement techniques for the inspection of the manufactured components. These measurement techniques are very sensitive to cooling liquids and lubricants which are essential for many manufacturing processes. Therefore, the measurement of the components is usually conducted in separate and clean laboratories and not directly in the manufacturing machine. This approach has some major drawbacks, e.g. high time consumption and no possibility for online process monitoring. In this article, a novel concept for the integration of high precision optical topography measurement systems into the manufacturing machine is introduced and compared to other concepts. The introduced concept uses a reservoir with cooling liquid in which the measurement object is immersed during the measurement. Thereby, measurement disturbance by splashing cooling liquids and lubricants can effectively be avoided.
Cite this paper: Mueller, T. , Poesch, A. and Reithmeier, E. (2016) Topography Measurement for Monitoring Manufacturing Processes in Harsh Conditions. Engineering, 8, 292-300. doi: 10.4236/eng.2016.85026.

[1]   van der Bijl, R.-J.M., Fähnle, O.W., van Brug, H. and Braat, J.J.M. (2000) Inprocess Monitoring of Grinding and Polishing of Optical Surfaces. Applied Optics, 39, 3300.

[2]   Fan, K.-C., Lee, M.-Z. and Mou, J.-I. (2002) On-Line Non-Contact System for Grinding Wheel Wear Measurement. International Journal of Advanced Manufacturing Technology, 19, 14-22.

[3]   Lim, H.S., Son, S.M., Wong, Y.S. and Rahman, M. (2007) Development and Evaluation of an On-Machine Optical Measurement Device. International Journal of Machine Tools and Manufacture, 47, 1556-1562.

[4]   Ji, Z. and Leu, M.C. (1989) Design of Optical Triangulation Devices. Optics & Laser Technology, 21, 339-341.

[5]   Donges, A. and Noll, R. (2015) Laser Measurement Technology: Fundamentals and Applications. Springer, Heidelberg.

[6]   Dorsch, R.G., Häusler, G. and Herrmann, J.M. (1994) Laser Triangulation: Fundamental Uncertainty in Distance Measurement. Applied Optics, 33, 1306-1314.

[7]   Beyerer, J., León, F.P. and Frese, C. (2012) Automatische Sichtprüfung. Springer, Heiderlberg.

[8]   Fisher, R.B. and Naidau, D.K. (1996) A Comparative Analysis of Algorithms for Determining the Peak Position of a Stripe to Sub-Pixel Accuracy. In: Sanz, J.L.C., Ed., Image Technologie: Advances in Image Processing, Multimedia and Machine Vision, Springer, Heidelberg, 385-404

[9]   Mueller, T., Poesch, A. and Reithmeier, E. (2015) Measurement Uncertainty of Microscopic Laser Triangulation on Technical Surfaces. Microscopy and Microanalysis, 21, 1443-1454.

[10]   Ayers, G.R. and Dainty, J.C. (1988) Interative Blind Deconvolution Method and Its Applications. Optics Letters, 13, 7.

[11]   Levin, A., Weiss, Y., Durand, F. and Freeman, W.T. (2009) Understanding and Evaluating Blind Deconvolution Algorithms. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops), Miami, 20-25 June 2009, 1964-1971.

[12]   Kundur, D. and Hatzinakos, D. (1996) Blind Image Deconvolution. IEEE Signal Processing Magazine, 13, 43-64.

[13]   Wallace, W., Schaefer, L.H. and Swedlow, J.R. (2001) A Workingperson’s Guide to Deconvolution in Light Microscopy. Biotechniques, 31, 1076-1097.

[14]   Krishnan, D., Tay, T. and Fergus, R. (2011) Blind Deconvolution Using a Normalized Sparsity Measure. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, 20-25 June 2011, 233-240.