Unreplicated factorial experimental designs for offline quality improvement and industrial process optimisation

Hager Farhoud and Lotfi Taleb

International Journal of Computational Economics and Econometrics, 2023, vol. 13, issue 2, 153-167

Abstract: A problem frequently encountered in the industrial offline improvement of quality is to identify from among many factors, those which are responsible for large changes in the quality characteristics, namely factors with active location and/or dispersion effects. Unreplicated experimental designs propose economic tools to discover what manufacturing conditions minimise product variation, maintain product measurements near the desired target value and make the product insensitive to environmental changes. However, no degrees of freedom are left to estimate the experimental error. To remove this dependency structure of residuals at the high and low levels of factor combinations, this study first addresses a synthesis and a critical analysis of existing location and dispersion effect identification methods. Second, a new method is proposed, and robustness check is based on real example and extensive simulation study. Third, practical issues are presented to enlighten investigators in their decision-making process.

Keywords: statistical process optimisation; quality engineering; screening designs; IER; EER; modified residuals. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=129977 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijcome:v:13:y:2023:i:2:p:153-167

Access Statistics for this article

More articles in International Journal of Computational Economics and Econometrics from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().