Prioritization of textile fabric defects using ordered weighted averaging operator

Saeidi, R. Ghazi; Oukil, Amar; Amin, Gholam R.; Raissi, Sadigh

doi:10.1007/s00170-014-6227-3

Cited by 18 publications

(4 citation statements)

References 37 publications

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“…The OWA weight vector γ can be generated in a way that echoes the subjectivity level of the DM. Although there are several approaches for generating these weights (see, e.g., Emrouznejad & Marra, 2014), the minimax disparity models are the most frequently used approaches (Saeidi et al, 2015). In our study, the following model, due to Wang & Parkan (2005), is used.…”

Section: Ordered Weighted Averagingmentioning

confidence: 99%

Energy-aware job scheduling in a multi-objective production environment – An integrated DEA-OWA model

Oukil

El-Bouri

Emrouznejad

2022

Computers & Industrial Engineering

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Section: Ordered Weighted Averagingmentioning

confidence: 99%

Energy-aware job scheduling in a multi-objective production environment – An integrated DEA-OWA model

Oukil

El-Bouri

Emrouznejad

2022

Computers & Industrial Engineering

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“…The OWA operator (Yager, ) with a weight vector π ∈ [0,1] K is a function

f (();, u, π) = \sum_{i = 1}^{K} π_{i} . {su}_{i}

where su i is the i th largest factor of the argument u = ( u 1 , …, u K ) and π i is the associated OWA weight, with i = 1,…, K and

\sum_{i = 1}^{K} π_{i} = 1

. Although there are several approaches for generating the weight vector π , the minimax disparity models remain the most commonly used (e.g., Saeidi, Oukil, Amin, & Raissi, ). In our study, we use the model due to Wang and Parkan () and defined as follows.…”

Section: A Two‐model Hybrid Approach For Rankingmentioning

confidence: 99%

A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective

Oukil

Govindaluri

2019

Manage Decis Econ

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This paper develops a hybrid multiattribute decision‐making methodology for ranking project proposals (PPs) through a judicious usage of historical data of completed projects to determine attribute weights, enabling elimination of problems associated with projected data such as cost and schedule overruns of real‐world projects. The weights generated from data envelopment analysis are explicitly utilized for ranking PPs while allowing subjectivity to be ingeniously incorporated into the decision process. The new approach is implemented for ranking 25 PPs, and the rankings it yields are found indifferent to the decision maker's attitude, which ascertains the robustness of the ranking methodology.

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“…Order weighted operation (OWA) model and data envelopment analysis (DEA) are applied for another fabric defects problem and Saeidi et al presented DEA approach to rank defects from the most to the least important and introduced a new method to prioritize the observed defects using the OWA operator (Saeidi, Oukil, & Amin, 2015).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Air Textured Warp Yarn Samples with TOPSIS method According to Quality Standards

Kaplan¹

2020

Proceedings of ‏The 3rd International Conference on Research in Business, Management and Economics

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The air textured warp yarn; produced from polyester fiber, is used as warp yarn in carpet weaving industry and is one of the yarns that form the floor of the carpet. Air textured warp yarn; that does not reflect the quality values, will cause elongation, shortening, stretching, shrinkage, irregularity problems in the carpet, during or after weaving process. Since these defects occur on the warp yarn, that forms the length of the carpet, directly affect the quality of carpet to be produced, therefore the purpose of the production in the companies producing this yarn, is based on the philosophy of producing quality products, before making a profit. For these reasons; certain criteria, determining the quality yarn, were identified during the production of air textured warp yarn, and standard production values were assigned, depending on those values. In this paper 649 samples of 800 Denier air-jet textured yarn subjected to a series of strength tests with the physical properties of the yarn. Tested yarn properties are count, elongation, shrinkage, tenacity, RKM (reisskilometer), force in kilograms. All tested properties of the yarns are ranked by TOPSIS method, which is a multicriteria decision-making method, based on certain weights. As a result all samples, from best to worst, shown to the decision-maker, to try to help which sample will be used in the next step of if a classification will be defined for quality.

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Prioritization of textile fabric defects using ordered weighted averaging operator

Cited by 18 publications

References 37 publications

Energy-aware job scheduling in a multi-objective production environment – An integrated DEA-OWA model

Energy-aware job scheduling in a multi-objective production environment – An integrated DEA-OWA model

A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective

Evaluation of Air Textured Warp Yarn Samples with TOPSIS method According to Quality Standards

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