Search Results

1 - 10 of 41 items :

  • "control chart" x
Clear All

for Quality Control”, New York, John Wiley & Sons. 8. Dumičić, K., Žmuk, B. (2011a), “Metode statističke kontrole kvalitete” (“Statistical Quality Control Methods”), in Dumičić, K., Bahovec, V. (Eds.), Poslovna statistika (Business Statistics), Zagreb, Element, pp. 459-539. 9. Dumičić, K., Žmuk, B. (2011b), “Monitoring delivery time with control charts”, in Katalinić. B. (Ed.), Annals of DAAAM for 2011 & Proceedings of the 22nd DAAAM International World Symposium, Vienna, Austria, November 24-26, 2011, Vienna, DAAAM International Vienna, pp. 1199-1200. 10. Gandy, A

REFERENCES Abbas, N., Zafar, R. F., Riaz, M., Hussain, Z., 2013. Progressive Mean Control Chart for Monitoring Process Location Parameter , Quality and Reliability Engineering International, 29(3), 357-367, DOI: 10.1002/qre.1386. ISSN 07488017. Bakir, S., Prater, T., Kiser, S., 2015. A Simple Nonparametric Quality Control Chart for Monitoring Students’ GPAs . SOP Transactions on Statistics and Analysis, 2015(1), 8-16, DOI: 10.15764/STSA.2015.01002 Bush, H.M., Chongfuangprinya, P., Chen, V. C., Sukchotrat, T., Kim, S. B., 2010. Nonparametric multivariate

References Cen, Y. (1996). Fuzzy quality and analysis on fuzzy probability, Fuzzy Sets and Systems 83(2): 283-290. Cheng, C.-B. (2005). Fuzzy process control: Construction of control charts with fuzzy numbers, Fuzzy Sets and Systems 154(2): 287-303. Couso, I., Dubois, D., Montes, S. and Sanchez, L. (2007). On various definitions of the variance of a fuzzy random variable, Proceedings of the 5th International Symposium on Imprecise Probabilities and Their Applications, Prague, Czech Republic, www.sipta.org/isipta07/proceedings/056.html. Dubois, D. and Prade, H

References Anbari, F. T. (2003). Earned value project management method and extensions. Project management journal , 34(4), 12-23. Fleming, Q. W., & Koppelman, J. M. (2016). Earned value project management. Newtown Square, Pennsylvania: Project Management Institute. Hansen, J. P. (2007). Population control charts for population data. Journal for Healthcare Quality , 29(1), 29-36. Jacob, D., (2003). Forecasting Project Schedule Completion with Earned Value Metrics, The Measurable News , 1, 7-9. Jones, G., & Govindaraju, K. (2001). A Graphical Method for

filter tests of share prices. Journal of Business, 42 (3), 321–325. 15. Dumičić, K., & Žmuk, B. (2011a). Metode statističke kontrole kvalitete. In K. Dumičić & V. Bahovec (Eds.), Poslovna statistika (pp. 459–539). Zagreb: Element. 16. Dumičić, K., & Žmuk, B. (2011b). Monitoring delivery time with control charts. In B. Katalinić (Ed.), Annals of DAAAM for 2011 & Proceedings of the 22nd DAAAM International World Symposium (pp. 1199–1200). Vienna: DAAAM International. 17. Fama, E. F., & Blume, M. E. (1965). Filter rules and stock-market trading. Journal of Business

Abstract

Measurement of dispersion and variation have been studied and evaluated in many applications. Volatility in the field of finance is an important measure as it directly impacts allocation, risk management, and valuation. Pitman Closeness criterion is used to compare estimators of standard deviation from equity returns in a control charting application. Three estimators are evaluated over the 30 DJIA component stocks in an effort to determine if one method of estimation has better performance within an application of control charting for identifying outliers. The study uses three sample sizes to also determine if the better estimator is sample size dependent.

QPI 2019, volume 1, issue 1, pp. 464-471 PROPOSAL OF METHODOLOGY FOR PRACTICAL APPLICATION OF NONPARAMETRIC CONTROL CHARTS doi: https://doi.org/10.2478/9783110680591-063 Date of submission of the article to the Editor: 06/05/2019 Date of acceptance of the article by the Editor: 28/05/2019 Darja Noskievičová1 – orcid id: 0000-0002-1154-712X Tereza Smajdorová1 1VŠB-TU Ostrava, Czech Republic Abstract: This paper deals with the methodology for practical application of nonparametric control charts. This topic is very important for two reasons: firstly

Abstract

The paper presents a study on the control of the canned fish seaming with the so-called double seam and statistical analysis of correctness of seaming. The use of standard control charts enabled observation and intervention in case irrelevant parameters occur to keep the stability of the process. Based on the analysis made in Statistica program, a moment could have been captured when a machine had to be regulated in case the value of parameters of the double seam decreased and it had to be concluded unanimously when the most important seaming tools (rolls) should be replaced. A problem that had been solved consists mainly in ensuring the stability of the process during constant monitoring of the seaming process of the canned food.

Abstract

The aim of the article is to present the case study of implementation of the example CAQ system, which allows to meet the requirements of IATF 16949:2016 and the VDA 6.1 standards in the field of statistical process control (SPC). The foundations of the CAQ systems concept and their specific requirements, especially for companies operating in the automotive industry, for which modern CAQ tools are necessary, in the described case based on the LEAN-QS program, are presented. The article presents the observations and results of the analysis of the operation of the quality assurance system in a company that is a supplier of car parts. One of the modules of the LEAN-QS program was implemented there, which makes it possible to meet the requirements of a certified quality management system. The effectiveness of the presented tool was demonstrated, allowing to meet industry requirements while minimizing resources necessary for supervision and proper implementation of the quality management system process, which in this case is the SPC.

Symposium on the Foundations of Computer Science, New York, NY, USA, pp. 616-623. Biau, G. and Devroye, L. and Lugosi, G. (2008). On the performance of clustering in Hilbert spaces IEEE Transactions on Information Theory 54 (2): 781-790. Bodnar, O. and Schmid, W. (2005). Multivariate control charts based on a projection approach Allgemeines Statistisches Archiv 89 (1): 75-93. Chandola, V., Banerjee, A. and Kumar, V. (2009). Anomaly detection: A survey, ACM Computing Surveys 41 (3): 15:1-15:58. Cramer, H. and Wold, H.(1936). Some theorems on distribution functions