Document Type : Research Paper
Authors
1 Department of Industrial Engineering, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran.
2 Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Abstract
Most qualitative characteristics cannot be easily reported numerically. In such cases, each product is inspected and usually divided into two conforming and nonconforming groups based on their qualitative characteristics. Since nowadays products and processes have generally several interdependent qualitative characteristics, it is necessary to use multivariate quality control methods to make the relationship between variables and their variations. To do this, the sampling of the considered qualitative characteristic is done at the specified time intervals to check the control of the process over time after drawing the considered statistic on the control chart. A common problem while sampling is measurement error. It affects the performance of control charts, impairs their ability to detect changes in the process, and increases the cost and time to search for out-of-control situations. In this paper, the effect of measurement error on the performance of the Multivariate Nonconforming Proportion (MNP) control chart has been evaluated based on the criterion of Average Run Length (ARL) for the first time. The results imply that the measurement error has a considerable impact on the performance of this chart. Also, the results indicate that if the defective items have been wrongly considered as correct items, we would have a higher ARL compared to an ideal and accurate system. On the other hand, if the system considers right items as defective, we will have a lower ARL than the ideal and accurate system. It is proved that if both errors (considering faulty items as correct ones and vice versa) occur simultaneously, the ARL will be reduced like the previous case.
Keywords
Main Subjects
- Montgomery, D. C. (2020). Introduction to statistical quality control. John Wiley & Sons.
- Montgomery, D. C., & Mastrangelo, C. M. (1991). Some statistical process control methods for autocorrelated data. Journal of quality technology, 23(3), 179-193.
- Champ, C. W., & Woodall, W. H. (1987). Exact results for Shewhart control charts with supplementary runs rules. Technometrics, 29(4), 393-399.
- Lowry, C. A., & Montgomery, D. C. (1995). A review of multivariate control charts. IIE transactions, 27(6), 800-810.
- Lu, X. S. (1998). Control chart for multivariate attribute processes. International journal of production research, 36(12), 3477-3489.
- Khammarnia, M., Ravangard, R., Ghanbari Jahromi, M., & Moradi, A. (2013). Survey of medical errors in Shiraz public hospitals. JHOSP, 13(3), 17-24. (In Persian). http://jhosp.tums.ac.ir/article-1-5153-fa.html.
- Rezaei, H. P., Habibi, S., & Fozounkhah, S. (2007). Information technology, an effective tool in reducing and preventing medical errors: suggestions for improvement. Health information management, 4(1), 89-98.
- Bennett, C. A. (1954). Effect of measurement error on chemical process control. Industrial quality control, 10(4), 17-20.
- Kanazuka, T. (1986). The effect of measurement error on the power of X-R charts. Journal of quality technology, 18(2), 91-95.
- Linna, K. W., Woodall, W. H., & Busby, K. L. (2001). The performance of multivariate control charts in the presence of measurement error. Journal of quality technology, 33(3), 349-355.
- Maravelakis, P., Panaretos, J., & Psarakis, S. (2004). EWMA chart and measurement error. Journal of applied statistics, 31(4), 445-455.
- Xiaohong, L., & Zhaojun, W. (2009). The CUSUM control chart for the autocorrelated data with measurement error. Chinese journal of applied probability and statistics, 25(5), 461-474.
- Abbasi, S. A. (2010). On the performance of EWMA chart in the presence of two-component measurement error. Quality engineering, 22(3), 199-213.
- Costa, A. F., & Castagliola, P. (2011). Effect of measurement error and autocorrelation on the X chart. Journal of applied statistics, 38(4), 661-673.
- Moameni, M., Saghaei, A., & Salanghooch, M. G. (2012). The effect of measurement error on X̃-R̃ fuzzy control charts. Engineering, technology & applied science research, 2(1), 173-176.
- Saghaei, A., Fatemi Ghomi, S. M. T., & Jaberi, S. (2014). The economic design of simple linear profiles. International journal of industrial engineering, 24(4), 405-412.
- Amiri, A., & Mohebbi, M. (2014). Economic-statistical design of EWMA-3 control chart for monitoring simple linear profiles. International journal of quality engineering and technology, 4(4), 290-314.
- Noorossana, R., & Zerehsaz, Y. (2015). Effect of measurement error on phase II monitoring of simple linear profiles. The international journal of advanced manufacturing technology, 79(9), 2031-2040.
- Ding, G., & Zeng, L. (2015). On the effect of measurement errors in regression-adjusted monitoring of multistage manufacturing processes. Journal of manufacturing systems, 36, 263-273.
- Daryabari, S. A., Hashemian, S. M., Keyvandarian, A., & Maryam, S. A. (2017). The effects of measurement error on the MAX EWMAMS control chart. Communications in statistics-theory and methods, 46(12), 5766-5778.
- Sabahno, H., Amiri, A., & Castagliola, P. (2018). Evaluating the effect of measurement errors on the performance of the variable sampling intervals Hotelling's T2 control charts. Quality and reliability engineering international, 34(8), 1785-1799.
- Sabahno, H., Amiri, A., & Castagliola, P. (2018). Performance of the variable parameters X control chart in presence of measurement errors. Journal of testing and evaluation, 47(1), 480-497.
- Montgomery, D. C. (2020). Introduction to statistical quality control. John Wiley & Sons.
)