A Regression Approach for Discovering Small Variation Around a Target

L. K. Chan and T. K. Mak

Journal of the Royal Statistical Society Series C, 1995, vol. 44, issue 3, 369-377

Abstract: In the rubber industry, experiments are performed to examine how certain output characteristics are related to the design factors in the development of a rubber compound for tyre tread. Traditional approaches focus on adjusting the mean of an output characteristic to a target value. Our aim is to search for levels of the design factors which minimize the between‐units variation of the output characteristic, subject to the constraint that the mean be still on target. In this regard a regression approach is now proposed and its relationship with some traditional methods, such as the ‘performance measure independent of adjustment’ (PERMIA), is examined. The regression approach enjoys the following properties: it permits a two‐step optimization, and a subsequent change in the targeted value can be easily accommodated by adjusting the variables identified in the second stage; it does not require the form of PERMIA to be known in advance; it is computationally simple, requiring only standard regression routines. Another example, dealing with effects of factors in the ability of a printing machine to apply colouring ink, is also given for illustration. The method, as a by‐product, suggests a suitable transformation of the response for the approach advocated by Box.

Date: 1995
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2307/2986043

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:bla:jorssc:v:44:y:1995:i:3:p:369-377

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().