Fuzzy quality functiondeployment approach using TOPSIS and analytic hierarchy process methods

Kavosi, Majid; Mavi, Reza Kiani

doi:10.1504/ijpqm.2011.039350

Cited by 10 publications

(1 citation statement)

References 65 publications

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“…Ding (2011) presented a F-TOPSIS method to improve the quality of selection decisions. There are few papers in the literature regarding QFD-TOPSIS (Memari et al ., 2019; Kwong and Bai, 2003; Bhattacharya et al ., 2005; Zandi and Tavana, 2011; Kavosi and Mavi, 2011). Dursun and Karsak (2013) proposed a fuzzy MCDM technique that leverages and uses the QFD concept for the supplier selection procedure.…”

Section: Literature Review: Supplier Selection Qfd Fuzzy Topsis and Fstmentioning

confidence: 99%

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

Sharma

Tripathy²

2023

TQM

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PurposeSupplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).Design/methodology/approachThe proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.FindingsA fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.Originality/valueQFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

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Section: Literature Review: Supplier Selection Qfd Fuzzy Topsis and Fstmentioning

confidence: 99%

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

Sharma

Tripathy²

2023

TQM

View full text Add to dashboard Cite

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A data driven decision model for assessing the enablers of quality dimensions: Context of industry 4.0

Kumar

Hossain

Fazio

et al. 2021

CIRP Journal of Manufacturing Science and Technology

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Prioritizing critical failure factors of IT projects with fuzzy analytic hierarchy process

Khanfar¹,

Mavi²,

Jie³

2018

AIP Conference Proceedings

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Fuzzy quality functiondeployment approach using TOPSIS and analytic hierarchy process methods

Cited by 10 publications

References 65 publications

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

A data driven decision model for assessing the enablers of quality dimensions: Context of industry 4.0

Prioritizing critical failure factors of IT projects with fuzzy analytic hierarchy process

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