Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, Cilt: 48 Sayı: 2, 510 - 520, 01.04.2019

Öz

Kaynakça

  • Alaeddini, A., Ghazanfari, M., and Nayeri, M. A. A hybrid fuzzy-statistical clustering approach for estimating the time of changes in fixed and variable sampling control charts. Information Sciences, 179(11):1769-1784. Including Special Issue on Chance Discovery, 2009.
  • Asai, K. Fuzzy Systems for Management. IOS Press, Amsterdam, The Netherlands, 1st edition, 1995.
  • Buckley, J. Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3):233-247, 1985.
  • Chen, S.-M., Yang, M.-W., Lee, L.-W., and Yang, S.-W. Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets. Expert Systems with Applications, 39(5):5295-5308, 2012.
  • Cheng, C.-B. Fuzzy process control: construction of control charts with fuzzy numbers. Fuzzy Sets and Systems, 154(2):287-303, 2005.
  • Faraz, A. and Shapiro, A. F. An application of fuzzy random variables to control charts. Fuzzy Sets and Systems, 161(20):2684–2694. Theme: Games, Optimization and Discrete Structures, 2010.
  • Gülbay, M. and Kahraman, C. Development of fuzzy process control charts and fuzzy unnatural pattern analyses. Computational Statistics & Data Analysis, 51(1):434-451. The Fuzzy Approach to Statistical Analysis, 2006.
  • Gülbay, M. and Kahraman, C. An alternative approach to fuzzy control charts: Direct fuzzy approach. Information Sciences, 177(6):1463-1480, 2007.
  • Gülbay, M., Kahraman, C., and Ruan, D. α-cut fuzzy control charts for linguistic data. International Journal of Intelligent Systems, 19(12):1173-1195, 2004.
  • Kanagawa, A., Tamaki, F., and Ohta, H. Control charts for process average and variability based on linguistic data. International Journal of Production Research, 31(4):913-922, 1993.
  • Kaya, I. and Kahraman, C. Process capability analyses based on fuzzy measurements and fuzzy control charts. Expert Systems with Applications, 38(4):3172-3184, 2011.
  • Laviolette, M., Seaman, J. W., Barrett, J. D., and Woodall, W. H. A probabilistic and statistical view of fuzzy methods. Technometrics, 37(3):249-261, 1995.
  • Mendel, J. Uncertain rule-based fuzzy systems : introduction and new directions. Springer, Cham, Switzerland, 2001.
  • Qin, J. and Liu, X. Multi-attribute group decision making using combined ranking value under interval type-2 fuzzy environment. Information Sciences, 297:293-315, 2015.
  • Raz, T. and Wang, J.-H. Probabilistic and membership approaches in the construction of control charts for linguistic data. Production Planning & Control, 1(3):147-157, 1990.
  • Şentürk, S. and Antucheviciene, J. Interval type-2 fuzzy c-control charts: An application in a food company. Informatica, 28(2):269-283, 2017.
  • Şentürk, S. and Erginel, N. Development of fuzzy x¯ -r and x¯ -s control charts using $\alpha$-cuts. Information Sciences, 179(10):1542-1551, 2009.
  • Senvar, O. and Kahraman, C. Fuzzy process capability indices using clement’s method for non-normal processes. Journal of Multiple-Valued Logic & Soft Computing, 22, 2014.
  • Shewhart,W. A. Economic control of quality of manufactured product. ASQ Quality Press, 1931.
  • Shu, M.-H. andWu, H.-C. Fuzzy x and r control charts: Fuzzy dominance approach. Computers & Industrial Engineering, 61(3):676-685, 2011.
  • Teksen, H. E. and Anagün, A. S. Type 2 fuzzy control charts using likelihood and deffuzzification methods. In Advances in Fuzzy Logic and Technology 2017, pages 405-417. Springer, 2017a.
  • Teksen, H. E. and Anagün, A. S. Type 2 fuzzy control charts using ranking methods. In The 5th International Fuzzy Systems Symposium 2017, 2017b.
  • Wang, J.-H. and Raz, T. On the construction of control charts using linguistic variables. International Journal of Production Research, 28(3):477-487, 1990.
  • Woodall, W., Tsui, K., and Tucker, G. A review of statistical and fuzzy control charts based on categorical data. Frontiers in Statistical Quality Control, 1997.
  • Zadeh, L. The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 8(3):199-249, 1975.

Interval type-2 fuzzy c-Control charts using ranking methods

Yıl 2019, Cilt: 48 Sayı: 2, 510 - 520, 01.04.2019

Öz

Control charts are important for process or product because they provide information about the control situation of process and product. Because of this feature, control charts are used in many fields. Information about the product and/or process, which is under control or not, can be provided by looking the control charts. Fuzzy numbers are used to reduce information losses in operations with crisp numbers. In control charts applications, especially for qualitative control charts, the fuzzy set theory reduces the information losses and provide more flexible decision-making process. In the literature, there are some fuzzy control charts with type-1 fuzzy sets but there are few studies about fuzzy control charts regarding the cases where the data are expressed by type-2 fuzzy sets. The purpose of the study is to create an innovation using the ranking methods, which has not used for control charts in accessible literature, for the fuzzy control charts with interval type-2 fuzzy sets. The fuzzy results are compared with the crisp results. This study introduces ranking methods as new approach to generate interval type-2 fuzzy control charts, which is a different field.

Kaynakça

  • Alaeddini, A., Ghazanfari, M., and Nayeri, M. A. A hybrid fuzzy-statistical clustering approach for estimating the time of changes in fixed and variable sampling control charts. Information Sciences, 179(11):1769-1784. Including Special Issue on Chance Discovery, 2009.
  • Asai, K. Fuzzy Systems for Management. IOS Press, Amsterdam, The Netherlands, 1st edition, 1995.
  • Buckley, J. Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3):233-247, 1985.
  • Chen, S.-M., Yang, M.-W., Lee, L.-W., and Yang, S.-W. Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets. Expert Systems with Applications, 39(5):5295-5308, 2012.
  • Cheng, C.-B. Fuzzy process control: construction of control charts with fuzzy numbers. Fuzzy Sets and Systems, 154(2):287-303, 2005.
  • Faraz, A. and Shapiro, A. F. An application of fuzzy random variables to control charts. Fuzzy Sets and Systems, 161(20):2684–2694. Theme: Games, Optimization and Discrete Structures, 2010.
  • Gülbay, M. and Kahraman, C. Development of fuzzy process control charts and fuzzy unnatural pattern analyses. Computational Statistics & Data Analysis, 51(1):434-451. The Fuzzy Approach to Statistical Analysis, 2006.
  • Gülbay, M. and Kahraman, C. An alternative approach to fuzzy control charts: Direct fuzzy approach. Information Sciences, 177(6):1463-1480, 2007.
  • Gülbay, M., Kahraman, C., and Ruan, D. α-cut fuzzy control charts for linguistic data. International Journal of Intelligent Systems, 19(12):1173-1195, 2004.
  • Kanagawa, A., Tamaki, F., and Ohta, H. Control charts for process average and variability based on linguistic data. International Journal of Production Research, 31(4):913-922, 1993.
  • Kaya, I. and Kahraman, C. Process capability analyses based on fuzzy measurements and fuzzy control charts. Expert Systems with Applications, 38(4):3172-3184, 2011.
  • Laviolette, M., Seaman, J. W., Barrett, J. D., and Woodall, W. H. A probabilistic and statistical view of fuzzy methods. Technometrics, 37(3):249-261, 1995.
  • Mendel, J. Uncertain rule-based fuzzy systems : introduction and new directions. Springer, Cham, Switzerland, 2001.
  • Qin, J. and Liu, X. Multi-attribute group decision making using combined ranking value under interval type-2 fuzzy environment. Information Sciences, 297:293-315, 2015.
  • Raz, T. and Wang, J.-H. Probabilistic and membership approaches in the construction of control charts for linguistic data. Production Planning & Control, 1(3):147-157, 1990.
  • Şentürk, S. and Antucheviciene, J. Interval type-2 fuzzy c-control charts: An application in a food company. Informatica, 28(2):269-283, 2017.
  • Şentürk, S. and Erginel, N. Development of fuzzy x¯ -r and x¯ -s control charts using $\alpha$-cuts. Information Sciences, 179(10):1542-1551, 2009.
  • Senvar, O. and Kahraman, C. Fuzzy process capability indices using clement’s method for non-normal processes. Journal of Multiple-Valued Logic & Soft Computing, 22, 2014.
  • Shewhart,W. A. Economic control of quality of manufactured product. ASQ Quality Press, 1931.
  • Shu, M.-H. andWu, H.-C. Fuzzy x and r control charts: Fuzzy dominance approach. Computers & Industrial Engineering, 61(3):676-685, 2011.
  • Teksen, H. E. and Anagün, A. S. Type 2 fuzzy control charts using likelihood and deffuzzification methods. In Advances in Fuzzy Logic and Technology 2017, pages 405-417. Springer, 2017a.
  • Teksen, H. E. and Anagün, A. S. Type 2 fuzzy control charts using ranking methods. In The 5th International Fuzzy Systems Symposium 2017, 2017b.
  • Wang, J.-H. and Raz, T. On the construction of control charts using linguistic variables. International Journal of Production Research, 28(3):477-487, 1990.
  • Woodall, W., Tsui, K., and Tucker, G. A review of statistical and fuzzy control charts based on categorical data. Frontiers in Statistical Quality Control, 1997.
  • Zadeh, L. The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 8(3):199-249, 1975.
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İstatistik
Bölüm İstatistik
Yazarlar

Hatice Ercan Tekşen 0000-0001-7315-0067

Ahmet Sermet Anagün 0000-0002-7106-746X

Yayımlanma Tarihi 1 Nisan 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 48 Sayı: 2

Kaynak Göster

APA Ercan Tekşen, H., & Anagün, A. S. (2019). Interval type-2 fuzzy c-Control charts using ranking methods. Hacettepe Journal of Mathematics and Statistics, 48(2), 510-520.
AMA Ercan Tekşen H, Anagün AS. Interval type-2 fuzzy c-Control charts using ranking methods. Hacettepe Journal of Mathematics and Statistics. Nisan 2019;48(2):510-520.
Chicago Ercan Tekşen, Hatice, ve Ahmet Sermet Anagün. “Interval Type-2 Fuzzy C-Control Charts Using Ranking Methods”. Hacettepe Journal of Mathematics and Statistics 48, sy. 2 (Nisan 2019): 510-20.
EndNote Ercan Tekşen H, Anagün AS (01 Nisan 2019) Interval type-2 fuzzy c-Control charts using ranking methods. Hacettepe Journal of Mathematics and Statistics 48 2 510–520.
IEEE H. Ercan Tekşen ve A. S. Anagün, “Interval type-2 fuzzy c-Control charts using ranking methods”, Hacettepe Journal of Mathematics and Statistics, c. 48, sy. 2, ss. 510–520, 2019.
ISNAD Ercan Tekşen, Hatice - Anagün, Ahmet Sermet. “Interval Type-2 Fuzzy C-Control Charts Using Ranking Methods”. Hacettepe Journal of Mathematics and Statistics 48/2 (Nisan 2019), 510-520.
JAMA Ercan Tekşen H, Anagün AS. Interval type-2 fuzzy c-Control charts using ranking methods. Hacettepe Journal of Mathematics and Statistics. 2019;48:510–520.
MLA Ercan Tekşen, Hatice ve Ahmet Sermet Anagün. “Interval Type-2 Fuzzy C-Control Charts Using Ranking Methods”. Hacettepe Journal of Mathematics and Statistics, c. 48, sy. 2, 2019, ss. 510-2.
Vancouver Ercan Tekşen H, Anagün AS. Interval type-2 fuzzy c-Control charts using ranking methods. Hacettepe Journal of Mathematics and Statistics. 2019;48(2):510-2.