Monitoring a bi-attribute high-quality process using a mixture probability distribution. Issue 12 (1st December 2022)
- Record Type:
- Journal Article
- Title:
- Monitoring a bi-attribute high-quality process using a mixture probability distribution. Issue 12 (1st December 2022)
- Main Title:
- Monitoring a bi-attribute high-quality process using a mixture probability distribution
- Authors:
- Rasouli, Mohammad
Shahriari, Hamid
Samimi, Yaser - Abstract:
- Abstract: High-quality processes with very low defect rates are usually modeled using a Poisson distribution. Considering any correlation between the number of defects on a unit and the fraction of nonconforming units, a bi-attribute process is introduced and the relationship between the two features is discussed in this research. A generalization of the Poisson distribution which is called k -inflated Poisson (KIP) distribution is derived to model these types of processes. Based on the KIP distribution, a two-parameter distribution, a sampling method is suggested for inspection of a high-quality process. The joint distribution of the bi-attribute high-quality process is also introduced and the correlation between its attributes is discussed. The results of numerical examples provided some perspective to the model and supported the theoretical findings that there is no significant correlation between the two features. Then a charting procedure is suggested for monitoring the two parameters of the KIP distribution.
- Is Part Of:
- Communications in statistics. Volume 51:Issue 12(2022)
- Journal:
- Communications in statistics
- Issue:
- Volume 51:Issue 12(2022)
- Issue Display:
- Volume 51, Issue 12 (2022)
- Year:
- 2022
- Volume:
- 51
- Issue:
- 12
- Issue Sort Value:
- 2022-0051-0012-0000
- Page Start:
- 7427
- Page End:
- 7443
- Publication Date:
- 2022-12-01
- Subjects:
- Bi-attribute processes -- High-quality processes -- k-inflated Poisson distribution (KIP) -- Ranked probability control (RPC)
Mathematical statistics -- Periodicals
Mathematical statistics -- Data processing -- Periodicals
Digital computer simulation -- Periodicals
519.5 - Journal URLs:
- http://www.tandfonline.com/toc/lssp20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/03610918.2020.1837164 ↗
- Languages:
- English
- ISSNs:
- 0361-0918
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3363.431000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24613.xml