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Showing 3 results for Talebi
Nabaz Esmaeilzadeh, Hooshang Talebi,
Volume 2, Issue 2 (2-2009)
Abstract
So far, the Plackett-Burman (PB) designs have been considered as saturated non-regular fractional factorial designs for screening purposes. Since introduction of the hidden projection of PB's by Wang and Wu (1995), the estimation capability of such projections onto a subset of factors has been investigated by many researchers. In this paper, by considering the search and estimation capability of a design, we introduce the post-stage search designs, using sparsity principle of factorial effects. That is, by the post-stage property of a design, we mean the capability of such a design in searching and estimating possible nonzero 3-factorial interactions along with estimation of the general mean, main effects and active 2-factor interaction effects, identified in the pre-stage. We show that a 12-runs PB projections onto 4 and 5 factors are post-stage search designs.
Haleh Nekoee, Hooshang Talebi,
Volume 4, Issue 2 (3-2011)
Abstract
Two designs, with N runs and k factors all with two levels are said to be isomorphic or equivalent if one is obtained from another by permuting rows, columns or/and changing the levels of one or more factors. When N and k increase the matter of isomorphic recognition of two designs will be complicated. Therefore it is essential to apply needed conditions which are able to recognize and separate non-isomorphic designs. It should be done in the least possible time. Majority of needed existed conditions in the literature review can’t meet the two objectives, maximum separation in minimum span, at the same time. In this paper, a new method has been used to present non-equivalent. This new method has been designed abased on choice and comparisons of one or some rows of design matrix. This new method hopefully has higher ability to recognize non-equivalence. Besides, the new method has lower calculation and therefore is able to determine non-equivalence of two designs.
Mr. Mohsen Motavaze, Dr. Hooshang Talebi,
Volume 17, Issue 1 (9-2023)
Abstract
Production of high-quality products necessitates identifying the most influential factors, among many factors, for controlling and reducing quality variation. In such a setting, the factorial designs are utilized to determine the active factors with maximal information and model an appropriate relation between the factors and the variable of interest. In this regard, robust parameter designs dividing the factors to control- and noise factors are efficient methods for offline quality control for stabilizing the quality variation in the presence of the noise factors. Interestingly, this could be achieved through exploiting active control by noise interactions. One needs to experiment with numerous treatments to detect the active interaction effects. Search designs are suggested to save treatments, and a superior one is recommended among the appropriate ones. To determine the superior design, one needs a design criterion; however, the existing criteria could be more beneficial for robust parameter designs. In this paper, we proposed a criterion to rank the search designs and determine the superior one.
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