### Abstract

We explain deviations away from the usual estimate of the expected number of false alarms per unit time in the use of a Statistical Process Control (SPC) chart. Using applied probability we develop an exact analytic expression for the expected number of false alarms per unit time. The derivation involves determining the expected value of a modulus function of a random variable. Results depend upon the probability distribution of a key random variable: the time from when an out-of-control signal is observed (and an assignable cause is present) until the process is put back into control. For the cases of normal and Erlang distributions, the usual estimate used in the design of economic control charts is biased somewhat low. The bias becomes more important when there is an appreciable chance of the process going out of control within a single inter-sampling interval.

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

Pages (from-to) | 5589-5599 |

Number of pages | 11 |

Journal | International Journal of Production Research |

Volume | 45 |

Issue number | 23 |

DOIs | |

State | Published - Dec 2007 |

Externally published | Yes |

### Fingerprint

### Keywords

- Control charts
- False alarms
- Modulus function

### ASJC Scopus subject areas

- Management Science and Operations Research
- Industrial and Manufacturing Engineering

### Cite this

*International Journal of Production Research*,

*45*(23), 5589-5599. https://doi.org/10.1080/00207540701325421

**A more accurate representation of the expected number of false alarms in statistical quality control.** / Silver, E. A.; Rohleder, T. R.

Research output: Contribution to journal › Article

*International Journal of Production Research*, vol. 45, no. 23, pp. 5589-5599. https://doi.org/10.1080/00207540701325421

}

TY - JOUR

T1 - A more accurate representation of the expected number of false alarms in statistical quality control

AU - Silver, E. A.

AU - Rohleder, T. R.

PY - 2007/12

Y1 - 2007/12

N2 - We explain deviations away from the usual estimate of the expected number of false alarms per unit time in the use of a Statistical Process Control (SPC) chart. Using applied probability we develop an exact analytic expression for the expected number of false alarms per unit time. The derivation involves determining the expected value of a modulus function of a random variable. Results depend upon the probability distribution of a key random variable: the time from when an out-of-control signal is observed (and an assignable cause is present) until the process is put back into control. For the cases of normal and Erlang distributions, the usual estimate used in the design of economic control charts is biased somewhat low. The bias becomes more important when there is an appreciable chance of the process going out of control within a single inter-sampling interval.

AB - We explain deviations away from the usual estimate of the expected number of false alarms per unit time in the use of a Statistical Process Control (SPC) chart. Using applied probability we develop an exact analytic expression for the expected number of false alarms per unit time. The derivation involves determining the expected value of a modulus function of a random variable. Results depend upon the probability distribution of a key random variable: the time from when an out-of-control signal is observed (and an assignable cause is present) until the process is put back into control. For the cases of normal and Erlang distributions, the usual estimate used in the design of economic control charts is biased somewhat low. The bias becomes more important when there is an appreciable chance of the process going out of control within a single inter-sampling interval.

KW - Control charts

KW - False alarms

KW - Modulus function

UR - http://www.scopus.com/inward/record.url?scp=35348917705&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=35348917705&partnerID=8YFLogxK

U2 - 10.1080/00207540701325421

DO - 10.1080/00207540701325421

M3 - Article

AN - SCOPUS:35348917705

VL - 45

SP - 5589

EP - 5599

JO - International Journal of Production Research

JF - International Journal of Production Research

SN - 0020-7543

IS - 23

ER -