Control charts and feedback adjustments for a jump disturbance model

Nasser H. Ruhhal, George Runger, Monica Dumitrescu

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

We compare the performance of repeated process adjustments to postponed (bounded) adjustments for a model other than the widely used, normal-theory integrated moving average model. We generalize to an interesting, yet practical, alternative jump disturbance model. This model allows the process mean to remain constant for a random time period before a disturbance changes it (and includes a parameter that specifies the rate of mean changes in the process). Because the postponed adjustment can be based on a control chart, these strategies are included. Known analytical results are summarized and simulation is used to extend the performance analysis of different control strategies. We argue that for many process-operating conditions adjustments can be postponed, but that the magnitude of the adjustment (the diligent reaction) is a critical component for success.

Original languageEnglish (US)
Pages (from-to)379-394
Number of pages16
JournalJournal of Quality Technology
Volume32
Issue number4
StatePublished - 2000

Fingerprint

Control Charts
Adjustment
Jump
Disturbance
Feedback
Moving Average Model
Process Mean
Model
Integrated Model
Performance Analysis
Control Strategy
Control charts
Generalise
Alternatives
Simulation

Keywords

  • Engineering Process Control
  • Feedback Adjustment
  • Statistical Process Control
  • Time Series

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Statistics and Probability
  • Management Science and Operations Research

Cite this

Control charts and feedback adjustments for a jump disturbance model. / Ruhhal, Nasser H.; Runger, George; Dumitrescu, Monica.

In: Journal of Quality Technology, Vol. 32, No. 4, 2000, p. 379-394.

Research output: Contribution to journalArticle

Ruhhal, Nasser H. ; Runger, George ; Dumitrescu, Monica. / Control charts and feedback adjustments for a jump disturbance model. In: Journal of Quality Technology. 2000 ; Vol. 32, No. 4. pp. 379-394.
@article{0e80f8f6e8e344e1ab081309e748f3b9,
title = "Control charts and feedback adjustments for a jump disturbance model",
abstract = "We compare the performance of repeated process adjustments to postponed (bounded) adjustments for a model other than the widely used, normal-theory integrated moving average model. We generalize to an interesting, yet practical, alternative jump disturbance model. This model allows the process mean to remain constant for a random time period before a disturbance changes it (and includes a parameter that specifies the rate of mean changes in the process). Because the postponed adjustment can be based on a control chart, these strategies are included. Known analytical results are summarized and simulation is used to extend the performance analysis of different control strategies. We argue that for many process-operating conditions adjustments can be postponed, but that the magnitude of the adjustment (the diligent reaction) is a critical component for success.",
keywords = "Engineering Process Control, Feedback Adjustment, Statistical Process Control, Time Series",
author = "Ruhhal, {Nasser H.} and George Runger and Monica Dumitrescu",
year = "2000",
language = "English (US)",
volume = "32",
pages = "379--394",
journal = "Journal of Quality Technology",
issn = "0022-4065",
publisher = "American Society for Quality",
number = "4",

}

TY - JOUR

T1 - Control charts and feedback adjustments for a jump disturbance model

AU - Ruhhal, Nasser H.

AU - Runger, George

AU - Dumitrescu, Monica

PY - 2000

Y1 - 2000

N2 - We compare the performance of repeated process adjustments to postponed (bounded) adjustments for a model other than the widely used, normal-theory integrated moving average model. We generalize to an interesting, yet practical, alternative jump disturbance model. This model allows the process mean to remain constant for a random time period before a disturbance changes it (and includes a parameter that specifies the rate of mean changes in the process). Because the postponed adjustment can be based on a control chart, these strategies are included. Known analytical results are summarized and simulation is used to extend the performance analysis of different control strategies. We argue that for many process-operating conditions adjustments can be postponed, but that the magnitude of the adjustment (the diligent reaction) is a critical component for success.

AB - We compare the performance of repeated process adjustments to postponed (bounded) adjustments for a model other than the widely used, normal-theory integrated moving average model. We generalize to an interesting, yet practical, alternative jump disturbance model. This model allows the process mean to remain constant for a random time period before a disturbance changes it (and includes a parameter that specifies the rate of mean changes in the process). Because the postponed adjustment can be based on a control chart, these strategies are included. Known analytical results are summarized and simulation is used to extend the performance analysis of different control strategies. We argue that for many process-operating conditions adjustments can be postponed, but that the magnitude of the adjustment (the diligent reaction) is a critical component for success.

KW - Engineering Process Control

KW - Feedback Adjustment

KW - Statistical Process Control

KW - Time Series

UR - http://www.scopus.com/inward/record.url?scp=0001094511&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0001094511&partnerID=8YFLogxK

M3 - Article

VL - 32

SP - 379

EP - 394

JO - Journal of Quality Technology

JF - Journal of Quality Technology

SN - 0022-4065

IS - 4

ER -