{"references": ["Automotive Industry Action Group (AIAG), Measurement Systems\nAnalysis Reference Manual. 3rd ed., Chrysler, Ford, General Motors\nSupplier Quality Requirements Task Force, 2002.", "J. M. Juran, F. M. Gyrna, Quality Planning and Analysis, McGraw-Hill,\nNew York, 1993.", "S. Senol, Measurement system analysis using designed experiments with\nminimum \u03b1-\u03b2 Risks and n. Measurement, 36, 131\u2013141, 2004.", "H. T. Lee, Cpk index estimation using fuzzy numbers. European Journal\nof Operational Research, 129, 683-688, 2001.", "P. K. Leung, F. Spiring, Adjusted action limits for Cpm based on\ndepartures from normality. International Journal of Production\nEconomics, 107, 237-249, 2007.", "A. Parchami, M. Mashinchi, A.R. Yavari, and H.R. Maleki, Process\nCapability Indices as Fuzzy Numbers. Austrian Journal of Statistics,\n34(4), 391\u2013402, 2005.", "A. Parchami, M. Mashinchi. Fuzzy estimation for process capability\nindices. Information Sciences, 177, 1452\u20131462, 2007.", "J.J. Buckley, Elementary Queuing Theory based on Possibility Theory.\nFuzzy Sets and Systems37 1990, pp. 43\u201352.", "J.J. Buckley, Y. Qu, (1990), On Using \u03b1 -Cuts to Evaluate Fuzzy\nEquations. Fuzzy Sets and Systems 38,309\u2013312.\n[10] J.J. Buckley, T. Feuring, Y. Hayashi, (2001), Fuzzy Queuing Theory\nRevisited. International Journal of Uncertainty, Fuzziness, and\nKnowledge-based Systems 9,527\u2013537.\n[11] J.J. Buckley, E. Eslami, Uncertain Probabilities \u0399: The Discrete Case;\nSoft Computing 2003a, pp. 500-505.\n[12] J.J. Buckley, E. Eslami, Uncertain Probabilities \u03a0: The Continuous\nCase; Soft Computing 2003b, pp. 500-505.\n[13] J.J. Buckley, Fuzzy Statistics: Hypothesis Testing; Soft Computing,\n2005a, (9) pp. 512-518."]}

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.