Conference Paper

A Fuzzy Modelling Approach to NSE Criterion on Robust Design

Volume: 03 Number: 1 August 31, 2019
EN

A Fuzzy Modelling Approach to NSE Criterion on Robust Design

Abstract

Dual response methodology is a natural and effective tool for a reliable and robust operation process or product in modern quality engineering. Therefore, many of quality improvement techniques based on dual response methodology focus on being on target and reducing system variability. This paper presents a fuzzy modelling approach based on the Nash-Sutcliffe efficiency for a dual response problem. The proposed approach aims to determine a set of operating conditions that maximize the degree of satisfaction due to the Nash-Sutcliffe efficiency in a quality improvement context. Additionally, the proposed approach is illustrated with a well-known design of experiment by comparing existing methods.

Keywords

References

  1. [1] G.E.P. Box and K.B. Wilson, On the Experimental Attainment of Optimum Conditions, J. Roy. Statist. Soc. Ser. B Metho. 13 (1951) 1-45.
  2. [2] G.G. Vining and R.H. Myers, Combining Taguchi and Response Surface Philosophies: A Dual Response Approach, J. Qual. Technol. 22 (1990) 38-45.
  3. [3] E. Del Castillo and D.C. Montgomery, A Nonlinear Programming Solution to the Dual Response Problem, J. Qual. Technol. 25 (1993) 199-204.
  4. [4] D.K.J. Lin and W. Tu, Dual Response Surface Optimization, J. Qual. Technol. 27 (1995) 34-39.
  5. [5] K. Kim and D.K.J. Lin, Dual Response Surface Optimization: A Fuzzy Modeling Approach, J. Qual. Technol. 30 (1998) 1-10.
  6. [6] M. Zeybek and O. Köksoy, A Fuzzy Modelling Approach to Robust Design via Loss Functions, Turkish Journal of Forecasting. 01 (2017) 40-45.
  7. [7] A.C. Shoemaker, K.L, Tsui, and C.F.J. Wu, Economical Experimentation Methods for Robust Parameter Design, Technometrics. 33 (1991) 415-427.
  8. [8] K.A. Copeland and P.R. Nelson, Dual Response Optimization via Direct Function Minimization, J. Qual. Technol. 28 (1996) 331-336.

Details

Primary Language

English

Subjects

Mathematical Sciences

Journal Section

Conference Paper

Authors

Publication Date

August 31, 2019

Submission Date

November 13, 2018

Acceptance Date

January 23, 2019

Published in Issue

Year 2019 Volume: 03 Number: 1

APA
Köksoy, O., & Zeybek, M. (2019). A Fuzzy Modelling Approach to NSE Criterion on Robust Design. Turkish Journal of Forecasting, 03(1), 1-6. https://izlik.org/JA33PH33YC
AMA
1.Köksoy O, Zeybek M. A Fuzzy Modelling Approach to NSE Criterion on Robust Design. TJF. 2019;03(1):1-6. https://izlik.org/JA33PH33YC
Chicago
Köksoy, Onur, and Melis Zeybek. 2019. “A Fuzzy Modelling Approach to NSE Criterion on Robust Design”. Turkish Journal of Forecasting 03 (1): 1-6. https://izlik.org/JA33PH33YC.
EndNote
Köksoy O, Zeybek M (August 1, 2019) A Fuzzy Modelling Approach to NSE Criterion on Robust Design. Turkish Journal of Forecasting 03 1 1–6.
IEEE
[1]O. Köksoy and M. Zeybek, “A Fuzzy Modelling Approach to NSE Criterion on Robust Design”, TJF, vol. 03, no. 1, pp. 1–6, Aug. 2019, [Online]. Available: https://izlik.org/JA33PH33YC
ISNAD
Köksoy, Onur - Zeybek, Melis. “A Fuzzy Modelling Approach to NSE Criterion on Robust Design”. Turkish Journal of Forecasting 03/1 (August 1, 2019): 1-6. https://izlik.org/JA33PH33YC.
JAMA
1.Köksoy O, Zeybek M. A Fuzzy Modelling Approach to NSE Criterion on Robust Design. TJF. 2019;03:1–6.
MLA
Köksoy, Onur, and Melis Zeybek. “A Fuzzy Modelling Approach to NSE Criterion on Robust Design”. Turkish Journal of Forecasting, vol. 03, no. 1, Aug. 2019, pp. 1-6, https://izlik.org/JA33PH33YC.
Vancouver
1.Onur Köksoy, Melis Zeybek. A Fuzzy Modelling Approach to NSE Criterion on Robust Design. TJF [Internet]. 2019 Aug. 1;03(1):1-6. Available from: https://izlik.org/JA33PH33YC

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