Author, Subjects, Keywords

Cited Author

 

 
   » By Author or Editor
 » Browse Author by Alphabet
 » By Journal
 » By Subjects
 » By Affiliations
 » Malaysian Journals
 » By Type
 » By Year
 » By Latest Additions
 
 
   » By Author
 » Top 20 Authors
 » Top 20 Article
 » Top Journal Cited
 » Top Article Cited
 » Journal Citation Statistics
 » Usage Since Sept 2007


 
 
 

Login | Create Account

Carta Kawalan EWMA dan Carta Kawalan CUSUM: Satu Perbandingan Prestasi Menggunakan ARL (EWMA Control Chart and CUSUM Control Chart: A Comparison of Performance Using ARL)

Norizan Mohamed, and Muhamad Safiih Lola, and Wan Muhamad Amir, and Teoh, Kooi Siam, (2004) Carta Kawalan EWMA dan Carta Kawalan CUSUM: Satu Perbandingan Prestasi Menggunakan ARL (EWMA Control Chart and CUSUM Control Chart: A Comparison of Performance Using ARL). Matematika, 20 (2). pp. 141-150. ISSN 01278274

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
216Kb

Official URL: http://www.fs.utm.my/matematika/images/stories/matematika/200420208.pdf

Affiliations

Kolej Universiti Sains dan Teknologi Malaysia, Jabatan Matematik
Kolej Universiti Sains dan Teknologi Malaysia, Jabatan Matematik
Kolej Universiti Sains dan Teknologi Malaysia, Jabatan Matematik
Kolej Universiti Sains dan Teknologi Malaysia, Jabatan Matematik

Abstract

EWMA (Exponentially Weighted Moving-Average) control charts and CUSUM (Cumulative Sum) control charts are widely used in industry for prosess and measurement control. This paper provides a computer implimentation of a fast and accurate algorithm in programming SAS (Statistical Analysis System) to compute average run length (ARL) for CUSUM and EWMA charts to monitor the process mean. The in-control ARL is set to be at 50, 100, 250, 500, 1000, 1500 dan 2000. The sensitive for optimal control EWMA and CUSUM in monitoring shift is then be analyze. The results from EWMA and CUSUM control charts for monitoring any small and large increases in process mean be discuss.

Item Type:Journal
Keywords:Average Run Length, Shift, EWMA (Exponentially Weighted Moving-Average), CUSUM (Cumulative Sum), optimal control
Subjects:Q Science, Computer Science
ID Code:5754

[1] S.L. Albin, L. Kang & G. Shea, An X and EWMA Chart for Individual Observation, Journal of Quality Technologi, 29(1997), 41-48.

[2] Mitra Amitava, Fundamentals of Quality Control and Improvement, 2nd edition, Macmillan Publishing Company, New York, 1998.

[3] S.V. Crowder, Design of EWMA Schemes, Journal of Quality Technology, 21(1989), 155-162.

[4] C. Montgomery Douglas, C. Runger George, F. Hubele Norma, Engineering Statistics, 2nd edition, John Wiley, New York, 2000, 448-470.

[5] C. Montgomery Douglas, C. Runger George, Applied Statistics and Probability for Engineers, 2nd edition, John Wiley, New York 1999, 754-776.

[6] C. Montgomery Douglas, Introduction to Statistical Quality Control, 4th edition, John Wiley, New York 2001, 153 206, 403-433.

[7] W.D. Ewan & K.W. Kemp, Sampling Ispection of Continuous Processes with no Autocorrelation between Successive Results, Biometrika, 47(3&4)(1960), 363–380.

[8] F.F. Gan, An Optimal Design of CUSUM Quality Control Charts, Journal of Quality Technology, 23(1991), 279-286.

[9] J.M. Lucas & M.S. Saccucci, Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements, Technometrics, 32(1)(1990), 1–29.

[10] E.S. Page, Continuous Inspection Schemes, Biometrica, 41(1954), 100–115.

[11] S.W. Roberts, Control Charts Based on Geometrics Moving Averages, Technometrics, 1(1959), 239–250.

[12] P. Cod Ronald, K. Smith Jeffrey , Applied Statistics and the SAS Programming Language, 4th edition, 1997.

Repository Staff Only: item control page