Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31442
Fuzzy Gauge Capability (Cg and Cgk) through Buckley Approach

Authors: Seyed Habib A. Rahmati, Mohsen Sadegh Amalnick


Different terms of the Statistical Process Control (SPC) has sketch in the fuzzy environment. However, Measurement System Analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works based on Buckley approach, imprecision and vagueness nature of the real world measurement are considered simultaneously. To do so, fuzzy version of the gauge capability (Cg and Cgk) are introduced. The method is also explained through example clearly.

Keywords: SPC, MSA, gauge capability, Cg, Cgk.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4722


[1] Automotive Industry Action Group (AIAG), Measurement Systems Analysis Reference Manual. 3rd ed., Chrysler, Ford, General Motors Supplier Quality Requirements Task Force, 2002.
[2] J. M. Juran, F. M. Gyrna, Quality Planning and Analysis, McGraw-Hill, New York, 1993.
[3] S. Senol, Measurement system analysis using designed experiments with minimum α-β Risks and n. Measurement, 36, 131–141, 2004.
[4] H. T. Lee, Cpk index estimation using fuzzy numbers. European Journal of Operational Research, 129, 683-688, 2001.
[5] P. K. Leung, F. Spiring, Adjusted action limits for Cpm based on departures from normality. International Journal of Production Economics, 107, 237-249, 2007.
[6] A. Parchami, M. Mashinchi, A.R. Yavari, and H.R. Maleki, Process Capability Indices as Fuzzy Numbers. Austrian Journal of Statistics, 34(4), 391–402, 2005.
[7] A. Parchami, M. Mashinchi. Fuzzy estimation for process capability indices. Information Sciences, 177, 1452–1462, 2007.
[8] J.J. Buckley, Elementary Queuing Theory based on Possibility Theory. Fuzzy Sets and Systems37 1990, pp. 43–52.
[9] J.J. Buckley, Y. Qu, (1990), On Using α -Cuts to Evaluate Fuzzy Equations. Fuzzy Sets and Systems 38,309–312.
[10] J.J. Buckley, T. Feuring, Y. Hayashi, (2001), Fuzzy Queuing Theory Revisited. International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems 9,527–537.
[11] J.J. Buckley, E. Eslami, Uncertain Probabilities Ι: The Discrete Case; Soft Computing 2003a, pp. 500-505.
[12] J.J. Buckley, E. Eslami, Uncertain Probabilities Π: The Continuous Case; Soft Computing 2003b, pp. 500-505.
[13] J.J. Buckley, Fuzzy Statistics: Hypothesis Testing; Soft Computing, 2005a, (9) pp. 512-518.