Skip to main content
Log in

Computer aided inspection: design of customer-oriented benchmark for noncontact 3D scanner evaluation

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Many different applications of online product inspections have found a significant advantage by the use of 3D scanners, especially when working with complex surfaces (free-form,…), where traditional inspection tools proved to have significant limitations. Unfortunately, there are not only success stories, but also several situations in which the approach towards 3D scanner technologies has been unsuccessful. This is mainly due to the fact that it is hard to understand which 3D scanner solution is the best to adopt and which working protocol is to be followed in order to obtain the best results from a specific application. These problems are often caused by the absence of a long expertise in 3D scanners and by the presence of inappropriate technical sheets. These last are, in fact, quite fragmented and inhomogeneous and only provide little information about the device behavior in the different working scenarios since they tend to be more oriented to the theoretical metrological performances. Most of the time, this information is not useful for users, who need to have a unique map showing both 3D scanner technical performances and their correlations to the different working scenarios in order to be able to compare the several available systems and to get a better understanding of their usage. In order to provide a solution to this problem, this paper proposes to create a customer benchmarking methodology that is a mixture of benchmark geometry designs and experiment sets. This benchmarking methodology will be focused on the simulation of a computer-aided inspection working scenario and carried out by using the quality function deployment method, in order to be oriented towards customer needs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Yau HT, Menq CH (1995) Automated CMM path planning for dimensional inspection of dies and moulds having complex surfaces. Int J Mach Tools Manuf 35:861–876

    Article  Google Scholar 

  2. Lartigue C, Mehdi C, Thibaut F (2006) Scan planning strategy for a general digitized surface. J Comput Inf Sci Eng 6:331

    Article  Google Scholar 

  3. Wu Y, Singh P, Kaucic R, Chen J, Little F (2007) Multimodal industrial inspection and analysis. J Comput Inf Sci Eng 7:102–107

    Article  Google Scholar 

  4. Sarfraz M (2006) Computer-aided reverse engineering using simulated evolution on NURBS. Virtual Phys Prototyping 1(4):243–257 December

    Article  Google Scholar 

  5. Creehan K, Bidanda B (2006) Computer-aided reverse engineering of the human musculoskeletal system. Virtual Phys Prototyping 1(2):83–91 June

    Article  Google Scholar 

  6. Marshall SJ, Whiteford DN, Rixon RC (2001) Assessing the performance of 3D whole body imaging systems. In: Proc 6th Numérisation 3D/Scanning 2001 Congress, Paris, 4–5 April 2001

  7. Rioux M (1997) Colour 3-D electronic imaging of the surface of the human body. Opt Lasers Eng 28:119–135 (NRC Also, SPIE Proceedings, Automatic Systems for the Identification and Inspection of Humans, San Diego, CA. July 28–29, 1994. Vol. 2277. pp. 42–54. NRC 3834)

    Article  Google Scholar 

  8. El-Hakim SF, Beraldin JA, Blais F (1995) A comparative evaluation of passive and active 3-D vision systems. In: Proc. Dig. Photogram., St-Petersburg, 25–30 June 1995

  9. Paakkari J, Moring I (1992) Method for evaluating the performance of range imaging devices. Proc. industrial applications of optical inspection, metrology, and sensing, SPIE-1821. SPIE, Bellingham, pp 350–356

    Google Scholar 

  10. Besl PJ (1988) Range imaging sensors. Mach Vis Appl 1:127–152. doi:10.1007/BF01212277

    Article  Google Scholar 

  11. Prieto F, Redarce T, Lepage R, Boulanger P (2002) An automated inspection system. Int J Adv Manuf Technol 19:917–925 doi:10.1007/s001700200104

    Article  Google Scholar 

  12. Kogure M, Akao Y (1983) Quality function deployment and Cwqc Japan. Qual Prog 16:25–29

    Google Scholar 

  13. Almannai B, Greenough R, Kayasdasdas J (2008) A decision support tool based on QFD and FMEA for the selection of manufacturing automation technologies. Robot Comput Integr Manuf 24(4):501–507 August

    Article  Google Scholar 

  14. Kwong CK, Chen Y, Bai H, Chan DSK (2007) A methodology of determining aggregated importance of engineering characteristics in QFD. Comput Ind Eng 53(4):667–679 November

    Article  Google Scholar 

  15. Asi (1987) Quality Function Deployment. Executive Briefing, American Supplier Institute Inc., Dearborn (Mi)

  16. Strand TC (1985) Optical three-dimensional sensing for machine vision. Opt Eng 24(1):33–40

    Google Scholar 

  17. Clark J, Wallace AM, Pronzato G (1998) Measuring range using triangulation sensors with variable geometry. IEEE Trans Robot Autom 14(1):54–60. doi:10.1109/70.660843

    Article  Google Scholar 

  18. Simple 3D (2006) 3D scanners, digitizers, and software for making 3D models and 3D measurements. http://www.simple3d.com

  19. Clark J (2000) Implementing non-contact digitization techniques within the mechanical deign process. Sens Rev 20(3):195–201

    Article  Google Scholar 

  20. Lockett S (1999) Reverse engineering: an overview and a real time industrial case study. Time Compress Technol 7(3):54–60

    Google Scholar 

  21. American National Standard for Automated Vision Systems – Performance Test – Measurement of Relative Position of Target Features in Two-Dimensional Space. ANSI/AVA A15.05/1 – 1989

  22. Urban GL, Hauser JR (1993) Design and marketing of new products. Prentice-Hall, Englewood Cliffs, pp 267–279 cap 10

    Google Scholar 

  23. Box GE, Hunter WG, Hunter JS, Hunter WG (2005) Statistics for experimenters: design, innovation, and discovery, 2nd edn. Wiley, New York (ISBN: 0471718130)

    MATH  Google Scholar 

  24. Kerzner H (2004) Advanced project management, 2nd edn. Wiley, New York (ISBN 978–0471472841 December 1)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Enrico Vezzetti.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Vezzetti, E. Computer aided inspection: design of customer-oriented benchmark for noncontact 3D scanner evaluation. Int J Adv Manuf Technol 41, 1140–1151 (2009). https://doi.org/10.1007/s00170-008-1562-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-008-1562-x

Keywords

Navigation