Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools

Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools

In semiconductor industries, it as a common problem for the manufacture to falsely reject good product, part or component in their production lines due to error measurement of their vision inspection system. This scenario is very costly to the manufacturers in term of cycle time, scrap and delivery...

Full description

Saved in:
Bibliographic Details
Main Author: Semposothy, Sevasothy
Format: Thesis
Language:English
English
Published: 2017
Subjects:
T Technology (General)
TS Manufactures
Online Access:http://eprints.utem.edu.my/id/eprint/22399/1/Investigation%20On%20Vision%20Lead%20Over%20Rejection%20For%20D-PAK%20Package%20At%20Testing%20Operation%20Using%20Seven%20Quality%20Control%20Tools%20-%20Sevasothy%20Semposothy%20-%2024%20Pages.pdf
http://eprints.utem.edu.my/id/eprint/22399/2/Investigation%20On%20Vision%20Lead%20Over%20Rejection%20For%20D-PAK%20Package%20At%20Testing%20Operation%20Using%20Seven%20Quality%20Control%20Tools%20-%20Sevasothy%20Semposothy.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utem-ep.22399
record_format uketd_dc
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Che Zainal, Nik Mohd Farid
topic T Technology (General)
TS Manufactures
spellingShingle T Technology (General)
TS Manufactures
Semposothy, Sevasothy
Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools
description In semiconductor industries, it as a common problem for the manufacture to falsely reject good product, part or component in their production lines due to error measurement of their vision inspection system. This scenario is very costly to the manufacturers in term of cycle time, scrap and delivery time. As a matter of fact, this problem can affect the credulity of the manufacturer from the customer’s perspective. Therefore, this project attempt to investigate the root cause of the falsely reject products which is known as over rejection for a semiconductor’s manufacturer in Melaka. Specifically, this project looked at over rejection for a lead to a integrated circuit device. Through this research, the root cause of the over rejection that are spring back soft 3D vision pedestal material, worn out pickup head and dirty 3D vision system mirror have been identified using Seven Quality Control tools. Counter measure to overcome those issues that are replacing vision pedestal material with a harder material, introduce the use of jig and clean the vision mirror using elastic or bended cotton stick have been implemented to reduce or eliminate the above mentioned problem. After implementing the counter measure, over rejection due to soft vision pedestal material has been totally eliminated. Whereas, the problem due to worn out pickup head and dirty vision system mirror have been significantly reduced to 65.7% and 61.5% respectively. In fact the vision lead reject has been tremendously declined from being top 13 to the top 2 the lowest reject in overall reject detected at testing operation of the production line.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Semposothy, Sevasothy
author_facet Semposothy, Sevasothy
author_sort Semposothy, Sevasothy
title Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools
title_short Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools
title_full Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools
title_fullStr Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools
title_full_unstemmed Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools
title_sort investigation on vision lead over rejection for d-pak package at testing operation using seven quality control tools
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Manufacturing Engineering
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/22399/1/Investigation%20On%20Vision%20Lead%20Over%20Rejection%20For%20D-PAK%20Package%20At%20Testing%20Operation%20Using%20Seven%20Quality%20Control%20Tools%20-%20Sevasothy%20Semposothy%20-%2024%20Pages.pdf
http://eprints.utem.edu.my/id/eprint/22399/2/Investigation%20On%20Vision%20Lead%20Over%20Rejection%20For%20D-PAK%20Package%20At%20Testing%20Operation%20Using%20Seven%20Quality%20Control%20Tools%20-%20Sevasothy%20Semposothy.pdf
_version_ 1747834016752467968
spelling my-utem-ep.223992022-03-30T08:04:06Z Investigation On Vision Lead Over Rejection For D-PAK Package At Testing Operation Using Seven Quality Control Tools 2017 Semposothy, Sevasothy T Technology (General) TS Manufactures In semiconductor industries, it as a common problem for the manufacture to falsely reject good product, part or component in their production lines due to error measurement of their vision inspection system. This scenario is very costly to the manufacturers in term of cycle time, scrap and delivery time. As a matter of fact, this problem can affect the credulity of the manufacturer from the customer’s perspective. Therefore, this project attempt to investigate the root cause of the falsely reject products which is known as over rejection for a semiconductor’s manufacturer in Melaka. Specifically, this project looked at over rejection for a lead to a integrated circuit device. Through this research, the root cause of the over rejection that are spring back soft 3D vision pedestal material, worn out pickup head and dirty 3D vision system mirror have been identified using Seven Quality Control tools. Counter measure to overcome those issues that are replacing vision pedestal material with a harder material, introduce the use of jig and clean the vision mirror using elastic or bended cotton stick have been implemented to reduce or eliminate the above mentioned problem. After implementing the counter measure, over rejection due to soft vision pedestal material has been totally eliminated. Whereas, the problem due to worn out pickup head and dirty vision system mirror have been significantly reduced to 65.7% and 61.5% respectively. In fact the vision lead reject has been tremendously declined from being top 13 to the top 2 the lowest reject in overall reject detected at testing operation of the production line. 2017 Thesis http://eprints.utem.edu.my/id/eprint/22399/ http://eprints.utem.edu.my/id/eprint/22399/1/Investigation%20On%20Vision%20Lead%20Over%20Rejection%20For%20D-PAK%20Package%20At%20Testing%20Operation%20Using%20Seven%20Quality%20Control%20Tools%20-%20Sevasothy%20Semposothy%20-%2024%20Pages.pdf text en public http://eprints.utem.edu.my/id/eprint/22399/2/Investigation%20On%20Vision%20Lead%20Over%20Rejection%20For%20D-PAK%20Package%20At%20Testing%20Operation%20Using%20Seven%20Quality%20Control%20Tools%20-%20Sevasothy%20Semposothy.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=108968 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering Che Zainal, Nik Mohd Farid 1. Ackaradejruangsri, P. 2012. Defining Thai Product Quality in the 21st Century. Ritsumeikan Journal of Asia Pacific. 2. AsgharAfsharJahanshahi, Mohammad Ali HajizadehGashti, Seyed Abbas Mirdamadi, Khaled Nawaser and Seyed Mohammad SadeqKhaksar, 2011. Study the Effects of Customer Service and Product Quality on Customer Satisfaction and Loyalty. International Journal of Humanities and Social Science. 3. Barbara Smith, Joicey Hurth, Lynda Pletcher, Evelyn Shaw, Kathy Whaley, Mary Peters and Glen Dunlap,2014. A Guide to the Implementation Process: Stages, Steps and Activities. ECTA Center 4. Chang Jiang Li, Zhong Zhang, IppeiNakamura,TakashiImamura,Tetsuo Miyake and HisanagaFugiwara, 2012. Developing a new automatic vision defect inspection for curved surface with highly specular reflection, Internal Journal of Innovative Computing Information and Control Volume 8. 5. C J Smith and KAdendorff, 1991. Advantages and limitations of an automated visual inspection system. S A JOLVLYlal 0·6 TndLWvualEnginevUng, VA£. 5, No 1 6. Deepak, D and Dhingra., 2016. Mechani Application of quality control tools in a bicycle industry: A case study. International Journal of Research in Engineering and Technology eISSN: 2319-1163pISSN: 2321-7308. 7. Der-BaauPerng . Cheng-ChuanChou. Shu-Ming Lee, 2006. Design and development of a new machine vision wire bonding inspection system. Springer Verlag London Limited 8. Erick Saldana.E.,RaulSiche. R, Mariano Luján. M, Quevedo.R ., 2013. Review: computer vision applied to the inspection and quality control of fruits and vegetables. Brazilian journal of Food Technology Euphemia F T Yuen and Sian S L Chan, 2010. The effect of retail service quality and product quality on customer loyalty. Journal of Database Marketing & Customer Strategy Management. 9. Fabiana R. Leta, Flávio F. Feliciano, Igor L. de Souza, Edson Cataldo , 2016. Discussing accuracy in an automatic measurement system using computer vision techniques. ABCM Symposium Series in Mechatranics 10. Gaurav Akrani,2013. What is product Quality? Definition meaning important. Kalyan City Life. 11. Harrychand D. Kalicharan,2014. The Effect And Influence Of Country-OfOrigin On Consumers’ Perception Of Product Quality And Purchasing Intentions. International Business & Economics Research Journal. Volume 13, Number 5. 12. Ismail Al Kamal, Student Member, IEEE, Mohamad Adnan Al-Alaoui, 2008. Online Machine Vision Inspection System for Detecting Coating Defects in Metal Lids. Proceedings of the International Multi-Conference of Engineers and Computer Scientists 2008 Vol II 13. Jain.T and Meenu., 2013. Automation and Integration of Industries through Computer Vision Systems. International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, pp. 963-970. 14. James.M.R and Robson.S., 2012. Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application. 15. Junhua Sun, HuabinHe andDebing Zeng, Global Calibration of Multiple Cameras Based onSphere Targets, www.mdpi.com/journal/sensors 16. Kishu Manghani,2011.Quality assurance: Importance of systems and standard operating procedures.www.Picronline.Organisation 17. K. Khalili, S.A. Razavi, D. Karimzadgan, 2005. High Resolution Measurements Using a Low Resolution System. Measurement Science Review, Volume 5, Section 1. 18. Labudzki.R and Legutko.S., 2012. Applications of Machine Vision, Faculty of Mechanical Engineering and Management,Institute of Mechanical Technology 19. Lutzow.S., 2008. New Berlin Publish Magazine: Solid state technology. 20. Luc Oth, Paul Furgale, Laurent Kneip and Roland Siegwart, 2013. Rolling Shutter Camera Calibration, CVF paper. 21. Lourakis, M. and Argyros A., 2005. Is levenberg-marquardt the most efficient Optimization algorithm for implementing bundle adjustment. Tenth IEEE International Conference on, volume 2, pages 1526 –1531 Vol. 2. 22. Mar.N.S.S, Fookes.C and Yarlagadda.C.P.K.D.V., 2009. Design of automatic vision-based inspection system for solder joint segmentation. Journal of achievement materials and manufacturing engineering. Volume 34 issue 2. 23. Magar,V.M. and Dr. Shinde,V.B., 2014. Application of 7 Quality Control (7 QC) Tools for Continuous Improvement of Manufacturing Processes International Journal of Engineering Research and General Science Volume 2, Issue 4 24. Margaret Rouse, 2017.Definition of Implementation. CRM Trends 2016: ASEAN. 25. MikellP.Groover, 2001. Automation, Production System and Computer- Integrated Manufacturing, Second Edition. Prentice Hall International. In c. 26. N.S.S. Mar, C. Fookes, P.K.D.V. Yarlagadda, Design of automatic vision-based inspection system for solder joint segmentation, Journal of achievement in material and manufacturing engineering,Volume 34, issue2. 27. Pratik J. Patel, Sanjay C. Shah and Sanjay Makwana, 2014. Application of Quality Control Tools in Taper Shank Drills Manufacturing Industry: A Case Study. Journal of Engineering Research and Applications. 28. Rebecca L Charles, Teegan L Johnson, Sarah R Fletcher,2015. The use of Job Aids for Visual Inspection in Manufacturing and Maintenance. Elsevier. ScienceDirect 29. Samadhan D. Bhosale, S.C.Shilwant and S.R. Patil, 2013. Quality improvement in manufacturing processes using SQC tools. International Journal of Engineering Research and Applications (IJERA). 30. ShaharudinJakpar, Angelyn Goh Sze Na, Anita Johari, KhinThanMyint, 2012. Examining the Product Quality Attributes That Influences Customer Satisfaction Most When the Price Was Discounted: A Case Study in Kuching Sarawak. International Journal of Business and Social Science. 31. Sokovic.M, Jovanovic. J,Krivokapic. Z and Vujovic. A., 2009. Journal of Mechanical Engineering 55(2009)5, Start Page-End Page UDC 658.5. 32. Soon.T.K, 2008. Infineon Technologies Malaysia 33. S. Rajasekar, P. Philominathan, V. Chinnathambi, 2013. Research Methodology. Arxiv.organisation 34. Stevenson.W.J and Chee Chuang.S.C.,2010. Operation Management. The McGraw-Hill Companies. Inc. 35. Sun.J.,He.H and D. Zeng ., 2016. Global Calibration of Multiple Cameras Based on Sphere Targets 36. Tim Bergin, John Cusack, Kris DeSment, 2010. Advantage of LED lighting in vision inspection system. QundTechinc. 37. Oth.L, Furgale.P, Kneip.L, and Siegwart.R., 2013. Rolling Shutter Camera Calibration 38. Xiaoa.Z.Z,b,c, Cheea.O and Asundi.A,. 2011.An accurate 3D inspection system using heterodyne multiple frequency phase-shifting Algorithm. 39. Varsha M. Magar and Dr. Vilas B. Shinde, 2014. Application of 7 Quality Control (7 QC) Tools for Continuous Improvement of Manufacturing Processes. International Journal of Engineering Research and General Science Volume 2, Issue 4. 40. Z. Zhang., 2004. Camera Calibration. Emerging Topics in Computer Vision, Prentice Hall Professional Technical Reference. pages 4-43. http://www.hanmisemi.com http://www.infineon.com/cms/en/product http://www.srm.com.my/Copyright © 2008 SRM Integration (M) Sdn. Bhd, http:// Vitrox Technologies.com

Similar Items