Measuring One-Sided Process Capability Index for Autocorrelated Data in the Presence of Random Measurement Errors

References

[1] M. Anis and K. Bera, Process capability cp assessment for auto-correlated data in the presence of measurement errors, Int. J. Reliab. Qual. Saf. Eng. 29 (2022), no. 6, Article ID 2250010. 10.1142/S0218539322500103Search in Google Scholar

[2] K. Bera and M. Anis, Process incapability index for autocorrelated data in the presence of measurement errors, Comm. Statist. Theory Methods (2023), 10.1080/03610926.2023.2220921. 10.1080/03610926.2023.2220921Search in Google Scholar

[3] A. F. B. Costa and P. Castagliola, Effect of measurement error and auto-correlation on the X ¯ chart, J. Appl. Stat. 38 (2011), no. 4, 661–673. 10.1080/02664760903563627Search in Google Scholar

[4] B. S. Gildeh and Z. A. Ganji, The effect of measurement error on the process incapability index, Comm. Statist. Theory Methods 49 (2020), no. 3, 552–566. 10.1080/03610926.2018.1543777Search in Google Scholar

[5] R. D. Guevara and J. A. Vargas, Comparison of process capability indices under autocorrelated data, Rev. Colombiana Estadíst. 30 (2007), no. 2, 301–316. Search in Google Scholar

[6] M. R. Maleki, A. Amiri and P. Castagliola, Measurement errors in statistical process monitoring: A literature review, Comput. Indus. Eng. 103 (2017), 316–329. 10.1016/j.cie.2016.10.026Search in Google Scholar

[7] H.-J. Mittag, Measurement error effects on the performance of process capability indices, Frontiers in Statistical Quality Control, Springer, Heidelberg (1997), 195–206. 10.1007/978-3-642-59239-3_15Search in Google Scholar

[8] D. C. Montgomery, Introduction to Statistical Quality Control, John Wiley & Sons, New York, 2020. Search in Google Scholar

[9] A. M. Mood, Introduction to the Theory of Statistics, McGraw-Hill, New York, 1950. Search in Google Scholar

[10] E. Nikzad, A. Amiri and F. Amirkhani, Estimating total and specific process capability indices in three-stage processes with measurement errors, J. Stat. Comput. Simul. 88 (2018), no. 15, 3033–3064. 10.1080/00949655.2018.1498096Search in Google Scholar

[11] W. L. Pearn and M.-Y. Liao, One-sided process capability assessment in the presence of measurement errors, Qual. Reliab. Eng. Int. 22 (2006), no. 7, 771–785. 10.1002/qre.727Search in Google Scholar

[12] S. C. Shongwe and J. Malela-Majika, A new variable sampling size and interval synthetic and runs-rules schemes to monitor the process mean of autocorrelated observations with measurement errors, Int. J. Indust. Eng. Comput. 11 (2020), no. 4, 607–626. 10.5267/j.ijiec.2020.4.003Search in Google Scholar

[13] S. C. Shongwe and J.-C. Malela-Majika, Combined effect of auto-correlation and measurement errors on the adaptive x¯ monitoring schemes, Trans. Inst. Measurement Control 43 (2021), no. 3, 537–548. 10.1177/0142331220935293Search in Google Scholar

[14] S. C. Shongwe, J.-C. Malela-Majika and P. Castagliola, On monitoring the process mean of autocorrelated observations with measurement errors using the w-of-w runs-rules scheme, Qual. Reliab. Eng. Int. 36 (2020), no. 3, 1144–1160. 10.1002/qre.2622Search in Google Scholar

[15] S. C. Shongwe, J.-C. Malela-Majika and P. Castagliola, The new synthetic and runs-rules schemes to monitor the process mean of autocorrelated observations with measurement errors, Comm. Statist. Theory Methods 50 (2021), no. 24, 5806–5835. 10.1080/03610926.2020.1737125Search in Google Scholar

[16] S. C. Shongwe, J.-C. Malela-Majika, P. Castagliola and T. Molahloe, Side-sensitive synthetic and runs-rules charts for monitoring AR(1) processes with skipping sampling strategies, Comm. Statist. Theory Methods 49 (2020), no. 17, 4248–4269. 10.1080/03610926.2019.1596284Search in Google Scholar

[17] S. C. Shongwe, J.-C. Malela-Majika and T. Molahloe, One-sided runs-rules schemes to monitor autocorrelated time series data using a first-order autoregressive model with skip sampling strategies, Qual. Reliab. Eng. Int. 35 (2019), no. 6, 1973–1997. 10.1002/qre.2487Search in Google Scholar

[18] H. Shore, Process capability analysis when data are autocorrelated, Qual. Eng. 9 (1997), no. 4, 615–626. 10.1080/08982119708919083Search in Google Scholar

[19] A. Srivastava, A. Chaturvedi and N. Kumar, Finite sample performance of an estimator of process capability index cpm for the autocorrelated data, Comm. Statist. Simulation Comput. (2021), 10.1080/03610918.2021.1962344. 10.1080/03610918.2021.1962344Search in Google Scholar

[20] J. Sun, S. Wang and Z. Fu, The effect of autocorrelated data on taguchi process capability index cpm based on ar (1) model, 2009 International Conference on Management and Service Science, IEEE Press, Piscataway (2009), 1–4. 10.1109/ICMSS.2009.5301174Search in Google Scholar

[21] F.-K. Wang and Y. Tamirat, Lower confidence bound for process-yield index s pk with autocorrelated process data, Qual. Technol. & Quant. Manag. 12 (2015), no. 2, 253–267. 10.1080/16843703.2015.11673380Search in Google Scholar

[22] N. F. Zhang, Estimating process capability indexes for autocorrelated data, J. Appl. Stat. 25 (1998), no. 4, 559–574. 10.1080/02664769823025Search in Google Scholar