Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company

Besufekad Legesse; Sisay Geremew

doi:doi:10.11648/j.ie.20210501.12

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Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company

Besufekad Legesse, Sisay Geremew

Published in Industrial Engineering (Volume 5, Issue 1)

Received: 26 April 2021 Accepted: 24 June 2021 Published: 23 August 2021

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Abstract

Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.

Published in	Industrial Engineering (Volume 5, Issue 1)
DOI	10.11648/j.ie.20210501.12
Page(s)	7-20
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

DMAIC Methodology, Cost of Poor Quality, Six Sigma

References

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[3]	Desai, D. A., Kotadiya, P. & Makwana, N., 2015. Curbing variations in packaging process through Six Sigma way in a large-scale food-processing industry. J IndEngInt, 11, pp. 119–129.
[4]	Gijo, E. V., Scaria, J. & Antony, J., 2011. Application of six sigma methodology to reduce defects of a grinding process, Quality and Reliability Engineering International, 27 (8), pp. 1221–1234.
[5]	James R. Evans, W. M. L., 2005. An Introduction to Six sigma and Process Improvement.
[6]	Kabir, E., Boby, S. M. M. I. & Lutfi, M., 2013. Productivity Improvement by using Six-Sigma.
[7]	Mijajlevski, A., 2013. The six sigma dmaic methodology in logistics. In Logistics international conference. pp. 227–232.
[8]	Mikel Harry, R. S., 2000. Six Sigma.
[9]	Pyzdek, T., 2003. The Six Sigma Handbook, McGraw Hill.
[10]	Schroeder, R. G. et al., 2008. Six Sigma: Definition and underlying theory §. Journal of Operations Management, 26, pp. 536–554.
[11]	Sharma, G. V. S. S. &Rao, P. S., 2014. A DMAIC approach for process capability improvement an engine crankshaft manufacturing process. Journal of Industrial Engineering International, 10 (65), pp. 1–11.
[12]	Shokri, A., Nabhani, F., & Bradley, G. (2015). Reducing the scrap rate in an electronic manufacturing SME through Lean Six Sigma methodology: An Action Research. IEEE Engineering Management Review. https://doi.org/10.1109/EMR.2019.2931184.
[13]	Stephen, P., 2004. Application of DMAIC to integrate Lean Manufacturing and Six Sigma. Virginia Polytechnic Institute and State University.
[14]	Yadav, A., & Sukhwani, V. K. (2016). Quality Improvement by using Six Sigma DMAIC in an Industry. 6 (6), 41–46.
[15]	Yadav, N., Mathiyazhagan, K., & Kumar, K. (2019). Application of Six Sigma to minimize the defects in the glass manufacturing industry: A case study. Journal of Advances in Management Research, 16 (4), 594–624. https://doi.org/10.1108/JAMR-11-2018-0102.
[16]	Yasin, A., 2014. Application of Lean Six Sigma for Process Improvement: the Case of Ethiopian Paper and Pulp S. C. (June).
[17]	Zhang, W. et al., 2009. Six Sigma: A Retrospective and Prospective Study Six Sigma: A Retrospective and Prospective Study. POMS.
[18]	Kumar, S. & Sosnoski, M., 2009. Using DMAIC Six Sigma to systematically improve shopfloor production quality and costs. International Journal of Productivity and Performance Management, 58 (3), pp. 254–273.

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APA Style

Besufekad Legesse, Sisay Geremew. (2021). Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company. Industrial Engineering, 5(1), 7-20. https://doi.org/10.11648/j.ie.20210501.12

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ACS Style

Besufekad Legesse; Sisay Geremew. Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company. Ind. Eng. 2021, 5(1), 7-20. doi: 10.11648/j.ie.20210501.12

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AMA Style

Besufekad Legesse, Sisay Geremew. Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company. Ind Eng. 2021;5(1):7-20. doi: 10.11648/j.ie.20210501.12

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@article{10.11648/j.ie.20210501.12,
  author = {Besufekad Legesse and Sisay Geremew},
  title = {Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company},
  journal = {Industrial Engineering},
  volume = {5},
  number = {1},
  pages = {7-20},
  doi = {10.11648/j.ie.20210501.12},
  url = {https://doi.org/10.11648/j.ie.20210501.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ie.20210501.12},
  abstract = {Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.},
 year = {2021}
}

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TY - JOUR
T1 - Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company
AU - Besufekad Legesse
AU - Sisay Geremew
Y1 - 2021/08/23
PY - 2021
N1 - https://doi.org/10.11648/j.ie.20210501.12
DO - 10.11648/j.ie.20210501.12
T2 - Industrial Engineering
JF - Industrial Engineering
JO - Industrial Engineering
SP - 7
EP - 20
PB - Science Publishing Group
SN - 2640-1118
UR - https://doi.org/10.11648/j.ie.20210501.12
AB - Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.
VL - 5
IS - 1
ER -

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Author Information

Besufekad Legesse

School of Mechanical and Industrial Engineering, Bahir Dar University, Bahir Dar, Ethiopia
Sisay Geremew

School of Mechanical and Industrial Engineering, Bahir Dar University, Bahir Dar, Ethiopia

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APA Style

Besufekad Legesse, Sisay Geremew. (2021). Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company. Industrial Engineering, 5(1), 7-20. https://doi.org/10.11648/j.ie.20210501.12

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ACS Style

Besufekad Legesse; Sisay Geremew. Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company. Ind. Eng. 2021, 5(1), 7-20. doi: 10.11648/j.ie.20210501.12

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AMA Style

Besufekad Legesse, Sisay Geremew. Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company. Ind Eng. 2021;5(1):7-20. doi: 10.11648/j.ie.20210501.12

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@article{10.11648/j.ie.20210501.12,
  author = {Besufekad Legesse and Sisay Geremew},
  title = {Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company},
  journal = {Industrial Engineering},
  volume = {5},
  number = {1},
  pages = {7-20},
  doi = {10.11648/j.ie.20210501.12},
  url = {https://doi.org/10.11648/j.ie.20210501.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ie.20210501.12},
  abstract = {Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.},
 year = {2021}
}

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