Developing Fuzzy Tool Capability Measurement System Analysis
الموضوعات :
Soroush Avakh Darestani
1
,
Neda Ghane
2
,
Yusof Ismail
3
,
Azam Moradi Tadi
4
1 - Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch Qazvin, Iran
2 - Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch Qazvin, Iran
3 - Faculty of Engineering, International Islamic University Malaysia
4 - Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran
الکلمات المفتاحية: fuzzy numbers, Measurement system analysis, Tool capability indexes,
ملخص المقالة :
Due to the existing competitive environment of global economy, many companies allocate their major financial and human resources to quality improvement. Since, using measurement tool is an essential component in quality analysis and highly depends on quality of measurement systems and their results; measurement systems applications after calibration are the most efficient methods in real operations. Thus, inherent changes of measurement tools can be studied by computing capability index of measurement tools. This paper aims to develop a fuzzy model for computing capability. Fuzzy model for computing capability (Cg ،Cgk) with data in the form of fuzzy triangular and trapezoidal numbers using MATLAB is developed and then a case study applying proposed method is presented. Finally, we compare presented results with classical outcomes and prove that fuzzy environment gives more flexibility, rather than classical environment.
Bojadziev, G. and Bojadziev, M. (1991), “Fuzzy sets, fuzzy logic, applications”. London, World Scientific.
Burdick, R.K., Allen, A.E. and Larsen, G.A. (2002), “Comparing Variability of Two Measurement Processes Using R&R Studies”, Journal of Quality Technology, 34, 97-105.
Cepova, L., Kovacikova, A., Cep, A., Klaput, P., Mizera, O. (2018), “ Measurement System Analyses – Gauge Repeatability and Reproducibility Methods”, MEASUREMENT SCIENCE REVIEW, 18(1), 20-27.
Fang, J.J. and Wang, P.S. (2005), “The Analysis of Gauge Repeatability and Reproducibility with Interaction between Operators and Parts”, Proceeding of the Fifth International Conference on Quality and Reliability, 9-11 August, Beijing.
Fang, J.J., Yang, J.S., Zhen, W.H., Wang, P.S., Lin, F.Z. and Giang, M.S. (2009), “The GR&R Study with Different Gauges and Operators”, Proceedings of the 2009 Taiwan Business and Management Conference, Tainan.
Faraz, A. and Shapiro, A.F. (2010), “An application of fuzzy random variables to control chart”, FuzzySets and System, 161, 2684-2694.
Ghazanfari, M. and Rezaee, M. (2006), “Introduction to the theory of fuzzy sets”, University of Science and Technology, Tehran.
Genta, G., Galetto, M. (2018), “Study of measurement process capability with non-normal data distributions”, 15th CIRP Conference on Computer Aided Tolerancing – CIRP CAT 2018, 385–390.
Hajipour, V., Kazemi, A. and Mousavi, S.M. (2013),“A fuzzy expert system to increase accuracy and precision in measurement system analysis”, Measurement, 46, 2770–2780.
Kazemi, A., Haleh, H., Hajipour, V. and Rahmati, S.H. (2010), “Developing a Method for Increasing Accuracy and Precision in Measurement System Analysis: A Fuzzy Approach”, Journal of Industrial Engineering, 3, 25-32.
Kaya, İ. and Çolak, M. "A Literature Review on Fuzzy Process Capability Analysis," Journal of Testing and Evaluation 48 (in press). https://doi.org/10.1520/JTE20180038.
Lee, C.C. (2005), “The Importance of Calibration”, Quality Magazine, 41, 63-65.
Montgomery, D.C. and Runger, G.C. (1993), “Gauge Capability and Designed Experiments Part I: Basic Methods. Quality Engineering”,Vol. 6, pp. 115-135.
Mandel, J. (1997), “Repeatability and Reproducibility for Pass/Fail Data”. Journal of Testing & Evaluation, 25, 151-153.
MahshidZ, R., Mansourvar, Z., NørgaardHansen, H, (2018), “Tolerance analysis in manufacturing using process capability ratio with measurement uncertainty”. Precision Engineering, 52, 201-210.
Ostadsharifmemar, A., Akhavan Niaki, T. (2008), “A Review and Evaluation of Statistical Process Control Methods in Monitoring Process Mean and Variance Simultaneously”. Journal of Industrial Engineering 1 , 1-8.
Pan, J.N. (2004), “Determination of Optimal Parameters for Gage Repeatability and Reproducibility Study”. International Journal of Quality and Reliability Management, 21, 672-682.
Refaie, A. (2010), “Bata Evaluating Measurement and Process Capabilities by GR&R with Four Quality Measures”. Measurement, 43, 842–851.
Runje, B., Novak, A., Razumić. A. (2017), “Measurement system analysis in production process”. XVII International Scientific Conference on Industrial Systems. Novi Sad, Serbia, October 4 – 6. 2017.
Yeh, T.M., Pai, F.Y. and Huang, C.W. (2015), “Using Fuzzy Theory in %GR&R and NDC of Measurement System Analysis”, Engineering, 7, 161-176.
Zadeh, L.A. (1965), “Fuzzy sets, Information and Control”, 8, 338–353.
