Nonlinear control charts for jump detection

T. Sastri, Juan B Valdes, B. Flores

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents a new class of nonlinear control charts which respond quickly to small shifts and jump patterns in tme series. The underlying disturbance models for the control charts are nonlinear extensions of the IMA(1,1) model. The Kalman filtering algorithm generates Bayesian estimates of the process level for the control chart plotting. The single-parameter chart is identical to the EWMA, while the two- and three-parameter designs are much more effective in detecting small shifts mixed with local trends. The nonlinear control charting scheme is also capable of detecting a mean shift in independent observation.

Original languageEnglish (US)
Pages (from-to)1023-1044
Number of pages22
JournalInternational Journal of Production Research
Volume34
Issue number4
StatePublished - Apr 1996
Externally publishedYes

Fingerprint

Jump
Control charts
Mean shift
Kalman filtering
Exponentially weighted moving average
Charts

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

Nonlinear control charts for jump detection. / Sastri, T.; Valdes, Juan B; Flores, B.

In: International Journal of Production Research, Vol. 34, No. 4, 04.1996, p. 1023-1044.

Research output: Contribution to journalArticle

Sastri, T. ; Valdes, Juan B ; Flores, B. / Nonlinear control charts for jump detection. In: International Journal of Production Research. 1996 ; Vol. 34, No. 4. pp. 1023-1044.
@article{02df6b48bfd24fb7866f1bfa9a84d845,
title = "Nonlinear control charts for jump detection",
abstract = "This paper presents a new class of nonlinear control charts which respond quickly to small shifts and jump patterns in tme series. The underlying disturbance models for the control charts are nonlinear extensions of the IMA(1,1) model. The Kalman filtering algorithm generates Bayesian estimates of the process level for the control chart plotting. The single-parameter chart is identical to the EWMA, while the two- and three-parameter designs are much more effective in detecting small shifts mixed with local trends. The nonlinear control charting scheme is also capable of detecting a mean shift in independent observation.",
author = "T. Sastri and Valdes, {Juan B} and B. Flores",
year = "1996",
month = "4",
language = "English (US)",
volume = "34",
pages = "1023--1044",
journal = "International Journal of Production Research",
issn = "0020-7543",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

TY - JOUR

T1 - Nonlinear control charts for jump detection

AU - Sastri, T.

AU - Valdes, Juan B

AU - Flores, B.

PY - 1996/4

Y1 - 1996/4

N2 - This paper presents a new class of nonlinear control charts which respond quickly to small shifts and jump patterns in tme series. The underlying disturbance models for the control charts are nonlinear extensions of the IMA(1,1) model. The Kalman filtering algorithm generates Bayesian estimates of the process level for the control chart plotting. The single-parameter chart is identical to the EWMA, while the two- and three-parameter designs are much more effective in detecting small shifts mixed with local trends. The nonlinear control charting scheme is also capable of detecting a mean shift in independent observation.

AB - This paper presents a new class of nonlinear control charts which respond quickly to small shifts and jump patterns in tme series. The underlying disturbance models for the control charts are nonlinear extensions of the IMA(1,1) model. The Kalman filtering algorithm generates Bayesian estimates of the process level for the control chart plotting. The single-parameter chart is identical to the EWMA, while the two- and three-parameter designs are much more effective in detecting small shifts mixed with local trends. The nonlinear control charting scheme is also capable of detecting a mean shift in independent observation.

UR - http://www.scopus.com/inward/record.url?scp=0030128529&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0030128529&partnerID=8YFLogxK

M3 - Article

VL - 34

SP - 1023

EP - 1044

JO - International Journal of Production Research

JF - International Journal of Production Research

SN - 0020-7543

IS - 4

ER -