Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 30 Sayı: 2, 117 - 125, 28.06.2020
https://doi.org/10.32710/tekstilvekonfeksiyon.598582

Öz

Kaynakça

  • Montgomery, D.C. (2009). Introduction to Statistical Quality Control, 6th edition. United States of America, New York, John Wiley and Sons.
  • Lim, S. A. H., Antony, J., He, Z., & Arshed, N. (2017). Critical observations on the statistical process control implementation in the UK food industry: A survey. International Journal of Quality & Reliability Management, 34(5), 684-700. https://doi.org/10.1108/IJQRM-03-2015-0035
  • Senturk, S., Erginel, N., Kaya, I., & Kahraman, C. (2014). Fuzzy exponentially weighted moving average control chart for univariate data with a real case application. Applied Soft Computing, 22, 1-10. https://doi.org/10.1016/j.asoc.2014.04.022
  • Tuerhong, G. & Kim, S. B. (2015). Comparison of Novelty Score‐Based Multivariate Control Charts. Communications in Statistics-Simulation and Computation, 44(5), 1126-1143. https://doi.org/10.1080/03610918.2013.809098
  • Li, C. I., Pan, J. N., & Huang, M. H. (2019). A New Demerit Control Chart for Monitoring the Quality of Multivariate Poisson Processes. Journal of Applied Statistics, 46(4), 680-699. https://doi.org/10.1080/02664763.2018.1510477
  • Rasouli, O. & Zarei, M. H. (2016). Monitoring and reducing patient dissatisfaction: A case study of an Iranian public hospital. Total Quality Management & Business Excellence, 27(5-6), 531-559. https://doi.org/10.1080/14783363.2015.1016869
  • Niazmand, K., Mirzazadeh, A. & Rezaie, K. (2014). A fuzzy SQFE approach in supplier's performance monitoring. International Journal of Production Research, 52(22), 6841-6862. https://doi.org/10.1080/00207543.2014.919417
  • Nembhard, D. A. & Nembhard, H.B. (2000). A Demerits Control Chart For Autocorrelated Data. Quality Engineering, 13(2), 179-190. http://doi.org/10.1080/08982110108918640
  • Shu, M. H., Chiu, C. C., Nguyen, T. L. & Hsu, B. M. (2014). A demerit-fuzzy rating system, monitoring scheme and classification for manufacturing processes. Expert Systems with Applications, 41(17), 7878-7888. https://doi.org/10.1016/j.eswa.2014.06.035
  • Ho, S. L., Xie, M. & Goh, T. N. (2003). Process Monitoring Strategies for Surface Mount Manufacturing Processes. International Journal of Flexible Manufacturing Systems, 15(2), 95-112. https://doi.org/10.1023/A:1024432723561
  • Hou S., Wang H. & Feng S. (2016). Attribute Control Chart Construction Based on Fuzzy Score Number. Symmetry, 8(12), 139. https://doi.org/10.3390/sym8120139
  • Chen, L. H. (2005). A demerit control chart with linguistic weights. Journal of Intelligent Manufacturing, 16(3), 349-359. https://doi.org/10.1007/s10845-005-7028-1
  • Cheng, C. B. (2005). Fuzzy process control: construction of control charts with fuzzy numbers. Fuzzy Sets and Systems, 154(2), 287-303. https://doi.org/10.1016/j.fss.2005.03.002
  • Yinelek, H. (2017). Design of Demerit Control Chart by Fuzzy c-Means Method and An Application in Textile Sector. MSc Thesis, Istanbul Technical University, Institute of Science and Technology, Istanbul.
  • Ansari A. & Riasi A. (2016). Customer Clustering Using a Combination of Fuzzy C-Means and Genetic Algorithms. International Journal of Business and Management, 11(7), 59-66. http://doi.org/10.5539/ijbm.v11n7p59
  • Dodge, H. F. (1928). A method of rating a manufactured product. The Bell System Technical Journal, 7(2), 350-368. https://doi.org/10.1002/j.1538-7305.1928.tb01229.x
  • Chimka J. R. & Arispe P. V. C. (2006). New Demerit Control Limits for Poisson Distributed Defects. Quality Engineering, 18(4), 461-467. https://doi.org/10.1080/08982110600817235
  • Jones, L. A., Woodall, W. H. & Conerly, M. D. (1999). Exact Properties of Demerit Control Charts. Journal of Quality Technology, 31(2), 207–216. https://doi.org/10.1080/00224065.1999.11979915

DESIGN OF DEMERIT CONTROL CHARTS WITH FUZZY C-MEANS CLUSTERING AND AN APPLICATION IN TEXTILE SECTOR

Yıl 2020, Cilt: 30 Sayı: 2, 117 - 125, 28.06.2020
https://doi.org/10.32710/tekstilvekonfeksiyon.598582

Öz



Companies use process control to detect and prevent defectrcts in production. One of the most commonly
used technique is control charts. To control multiple dimensions of quality on
one control chart, multivariable control charts, control charts for attributes
and demerit control charts are widely used. In this study, we use demerit
control charts to monitor multiple defect types and propose to employ fuzzy
c-means method to cluster the defect types based on pre-specified criteria. The
criteria are chosen to represent the severity of defect types and specified as:
(i) number of scraps, (ii) number of reworks and (iii) time of rework. In order
to test the proposed method, u and c attribute control charts and demerit
control charts for six instances in a textile company are used and compared. It
is observed that both the scrap and the repair rates are decreased when the
proposed method of demerit control chart is used.

Kaynakça

  • Montgomery, D.C. (2009). Introduction to Statistical Quality Control, 6th edition. United States of America, New York, John Wiley and Sons.
  • Lim, S. A. H., Antony, J., He, Z., & Arshed, N. (2017). Critical observations on the statistical process control implementation in the UK food industry: A survey. International Journal of Quality & Reliability Management, 34(5), 684-700. https://doi.org/10.1108/IJQRM-03-2015-0035
  • Senturk, S., Erginel, N., Kaya, I., & Kahraman, C. (2014). Fuzzy exponentially weighted moving average control chart for univariate data with a real case application. Applied Soft Computing, 22, 1-10. https://doi.org/10.1016/j.asoc.2014.04.022
  • Tuerhong, G. & Kim, S. B. (2015). Comparison of Novelty Score‐Based Multivariate Control Charts. Communications in Statistics-Simulation and Computation, 44(5), 1126-1143. https://doi.org/10.1080/03610918.2013.809098
  • Li, C. I., Pan, J. N., & Huang, M. H. (2019). A New Demerit Control Chart for Monitoring the Quality of Multivariate Poisson Processes. Journal of Applied Statistics, 46(4), 680-699. https://doi.org/10.1080/02664763.2018.1510477
  • Rasouli, O. & Zarei, M. H. (2016). Monitoring and reducing patient dissatisfaction: A case study of an Iranian public hospital. Total Quality Management & Business Excellence, 27(5-6), 531-559. https://doi.org/10.1080/14783363.2015.1016869
  • Niazmand, K., Mirzazadeh, A. & Rezaie, K. (2014). A fuzzy SQFE approach in supplier's performance monitoring. International Journal of Production Research, 52(22), 6841-6862. https://doi.org/10.1080/00207543.2014.919417
  • Nembhard, D. A. & Nembhard, H.B. (2000). A Demerits Control Chart For Autocorrelated Data. Quality Engineering, 13(2), 179-190. http://doi.org/10.1080/08982110108918640
  • Shu, M. H., Chiu, C. C., Nguyen, T. L. & Hsu, B. M. (2014). A demerit-fuzzy rating system, monitoring scheme and classification for manufacturing processes. Expert Systems with Applications, 41(17), 7878-7888. https://doi.org/10.1016/j.eswa.2014.06.035
  • Ho, S. L., Xie, M. & Goh, T. N. (2003). Process Monitoring Strategies for Surface Mount Manufacturing Processes. International Journal of Flexible Manufacturing Systems, 15(2), 95-112. https://doi.org/10.1023/A:1024432723561
  • Hou S., Wang H. & Feng S. (2016). Attribute Control Chart Construction Based on Fuzzy Score Number. Symmetry, 8(12), 139. https://doi.org/10.3390/sym8120139
  • Chen, L. H. (2005). A demerit control chart with linguistic weights. Journal of Intelligent Manufacturing, 16(3), 349-359. https://doi.org/10.1007/s10845-005-7028-1
  • Cheng, C. B. (2005). Fuzzy process control: construction of control charts with fuzzy numbers. Fuzzy Sets and Systems, 154(2), 287-303. https://doi.org/10.1016/j.fss.2005.03.002
  • Yinelek, H. (2017). Design of Demerit Control Chart by Fuzzy c-Means Method and An Application in Textile Sector. MSc Thesis, Istanbul Technical University, Institute of Science and Technology, Istanbul.
  • Ansari A. & Riasi A. (2016). Customer Clustering Using a Combination of Fuzzy C-Means and Genetic Algorithms. International Journal of Business and Management, 11(7), 59-66. http://doi.org/10.5539/ijbm.v11n7p59
  • Dodge, H. F. (1928). A method of rating a manufactured product. The Bell System Technical Journal, 7(2), 350-368. https://doi.org/10.1002/j.1538-7305.1928.tb01229.x
  • Chimka J. R. & Arispe P. V. C. (2006). New Demerit Control Limits for Poisson Distributed Defects. Quality Engineering, 18(4), 461-467. https://doi.org/10.1080/08982110600817235
  • Jones, L. A., Woodall, W. H. & Conerly, M. D. (1999). Exact Properties of Demerit Control Charts. Journal of Quality Technology, 31(2), 207–216. https://doi.org/10.1080/00224065.1999.11979915
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Giyilebilir Malzemeler
Bölüm Makaleler
Yazarlar

Hülya Yılmaz 0000-0002-5415-5708

Seda Yanık

Yayımlanma Tarihi 28 Haziran 2020
Gönderilme Tarihi 30 Temmuz 2019
Kabul Tarihi 22 Mayıs 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 30 Sayı: 2

Kaynak Göster

APA Yılmaz, H., & Yanık, S. (2020). DESIGN OF DEMERIT CONTROL CHARTS WITH FUZZY C-MEANS CLUSTERING AND AN APPLICATION IN TEXTILE SECTOR. Textile and Apparel, 30(2), 117-125. https://doi.org/10.32710/tekstilvekonfeksiyon.598582

No part of this journal may be reproduced, stored, transmitted or disseminated in any forms or by any means without prior written permission of the Editorial Board. The views and opinions expressed here in the articles are those of the authors and are not the views of Tekstil ve Konfeksiyon and Textile and Apparel Research-Application Center.