Nothing Special   »   [go: up one dir, main page]

Skip to main content

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 328))

  • 2294 Accesses

Abstract

This paper addresses the utility of intelligent autonomous robotic arm for automatic removal of defective products in an industry. The task can be performed in two steps, finding the defective product with digital image processing and removal of defective part from the products. The image is regularly obtained and compared with the standard image. The defective product is sorted out based on threshold value between the real image and standard image. After detection of defective product, it is sorted out with the help of robotic arm and placed in the defective lot.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Chang, C.-Y., Lin, S.-Y., Jeng, M.: Using a Two-layer Competitive Hopfield Neural Network for Semiconductor Wafer Defect Detection. In: Proceedings of the IEEE International Conference on Automation Science and Engineering, Edmonton, Canada, August 1-2, pp. 301–306 (2005)

    Google Scholar 

  2. Robinson, A.P., Lewin, P.L., Swingler, S.G.: Detection of Manufacturing Defects in Polymeric Cable Joint Insulation using X-rays. In: Conference Record of the IEEE International Symposium on Electrical Insulation, pp. 34–37 (2006)

    Google Scholar 

  3. Priya, S., Kumar, T.A., Paul, V.: A Novel Approach to Fabric Defect Detection Using Digital Image Processing. In: Proceedings of International Conference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN 2011), pp. 228–232 (2011)

    Google Scholar 

  4. Clement, W.I.: An Instructional Robotics and Machine Vision Laboratory. IEEE Transactions on Education 37(I), 87–90 (1994)

    Article  Google Scholar 

  5. Garcia, G.J., Pomares, J., Torres, F.: Automatic robotic tasks in unstructured environments using an image path tracker. Control Engineering Practice 17, 597–608 (2009)

    Article  Google Scholar 

  6. Kelly, R., Carelli, R., Nasisi, O., Kuchen, B., Reyes, F.: Stable visual servoing of camera-in-hand robotic systems. IEEE-ASME Transactions on Mechatronics 5, 39–48 (2000)

    Article  Google Scholar 

  7. Reyes, J.F., Chiang, L.: Location and Classification of Moving Fruits In Real Time with A Single Color Camera. Chilean Journal of Agricultural Research 69, 179–187 (2009)

    Article  Google Scholar 

  8. Wang, H., Cao, Q., Masateru, N., Bao, J.: Image processing and robotic techniques in plug seedling production. Transactions of the Chinese Society of Agricultural Machinery 30, 57–62 (1999)

    Google Scholar 

  9. Zhang, Y., Wang, Y., Zuo, M.J., Wang, X.: Ultrasonic Time Of Flight Diffraction Crack Size Identification Based on Cross Correlation. In: Canadian Conference on Electrical and Computer Engineering CCECE/CCGEI IEEE, pp. 1737–1780 (2008)

    Google Scholar 

  10. Wang, C.-C., Jiang, B.C., Lin, J.-Y., Chu, C.-C.: Machine Vision-Based Defect Detection in IC Images Using the Partial Information Correlation Coefficient. IEEE Transactions on Semiconductor Manufacturing 26(3), 378–384 (2013)

    Article  Google Scholar 

  11. Laddha, N.R., Thakare, A.P.: A Review on Serial Communication by UART. International Journal of Advanced Research in Computer Science and Software Engineering 3(1), 366–369 (2013)

    Google Scholar 

  12. Seelye, M.: Camera-in-hand robotic system for remote monitoring of plant growth in a laboratory. In: 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Birender Singh .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Singh, B., Chandra, M., Kandru, N. (2015). Removal of Defective Products Using Robots. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 328. Springer, Cham. https://doi.org/10.1007/978-3-319-12012-6_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12012-6_41

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12011-9

  • Online ISBN: 978-3-319-12012-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics