### Abstract

The use of three probability distributions to model the time to failure in an economic model of a multivariate quality control procedure is investigated. A discrete-time Markov (geometric) model is developed, as well as two non-Markovian (Poisson and logarithmic series) models. Numerical examples are presented which indicate that both the Markov assumption and the shape of the distribution of time to failure are of considerable importance in determining the optimal test parameters.

Original language | English (US) |
---|---|

Title of host publication | AIIE Trans |

Pages | 55-61 |

Number of pages | 7 |

Volume | 6 |

Edition | 1 |

State | Published - Mar 1974 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*AIIE Trans*(1 ed., Vol. 6, pp. 55-61)

**ALTERNATIVE PROCESS MODELS IN THE ECONOMIC DESIGN OF T**2 CONTROL CHARTS.** / Heikes, Russell G.; Montgomery, Douglas; Yeung, Jimmy Y H.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*AIIE Trans.*1 edn, vol. 6, pp. 55-61.

}

TY - CHAP

T1 - ALTERNATIVE PROCESS MODELS IN THE ECONOMIC DESIGN OF T**2 CONTROL CHARTS.

AU - Heikes, Russell G.

AU - Montgomery, Douglas

AU - Yeung, Jimmy Y H

PY - 1974/3

Y1 - 1974/3

N2 - The use of three probability distributions to model the time to failure in an economic model of a multivariate quality control procedure is investigated. A discrete-time Markov (geometric) model is developed, as well as two non-Markovian (Poisson and logarithmic series) models. Numerical examples are presented which indicate that both the Markov assumption and the shape of the distribution of time to failure are of considerable importance in determining the optimal test parameters.

AB - The use of three probability distributions to model the time to failure in an economic model of a multivariate quality control procedure is investigated. A discrete-time Markov (geometric) model is developed, as well as two non-Markovian (Poisson and logarithmic series) models. Numerical examples are presented which indicate that both the Markov assumption and the shape of the distribution of time to failure are of considerable importance in determining the optimal test parameters.

UR - http://www.scopus.com/inward/record.url?scp=0016036569&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0016036569&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:0016036569

VL - 6

SP - 55

EP - 61

BT - AIIE Trans

ER -