A fuzzy-QFD approach to supplier selection

Bevilacqua, Maurizio; Ciarapica, Filippo Emanuele; Giacchetta, Giancarlo

doi:10.1016/j.pursup.2006.02.001

Cited by 332 publications

(171 citation statements)

References 60 publications

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“…Fuzzy logic is based on a set theory. It comprises of a membership function within the interval [0,1] which express the level of significance of an element for being the member of the set (Bevilacqua, Ciarapica, & Giacchetta, 2006). A feature of fuzzy logic which is of particular importance in expert systems is that it provides a systematic structure for dealing with fuzzy values, e.g., most, many, few, not very many, etc.…”

Section: Fuzzy Logicmentioning

confidence: 99%

A fuzzy MADM approach for project selection: a six sigma case study

Rathi¹,

Khanduja²,

Sharma³

2016

10.5267/j.dsl

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Six Sigma is a strategic approach of significant value in achieving overall excellence. It helps to accomplish the organizations strategic aim through the effectual use of project controlled methodology. As Six Sigma is a project controlled approach, it is necessary to prioritize projects which give utmost economic benefits to the firm. In real practice, Six Sigma projects selection is very tough assignment because poor project selection also happens even in the well-managed organizations and this can weaken the success and trustworthiness of the Six Sigma practice. The present study aims to develop a project selection approach based on a combination of fuzzy and MADM technique to help organizations determine proper Six Sigma projects and identify the priority of these projects mainly in automotive companies. VIKOR and TOPSIS methods have been used to select the proper Six Sigma project composed with fuzzy logic. In this context, seven critical parameters have been considered for selection of finest alternative. The weights of evaluation criteria are obtained using the MDL (modified digital logic) method and final ranking is calculated through primacy index obtained by using fuzzy based VIKOR and TOPSIS methodology. A factual case study from automotive industry is used to investigate the efficacy of the planned approach.

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Section: Fuzzy Logicmentioning

confidence: 99%

A fuzzy MADM approach for project selection: a six sigma case study

Rathi¹,

Khanduja²,

Sharma³

2016

10.5267/j.dsl

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“…Various conceptual or empirical methodologies regarding this topic have been developed [20][21][22]. The complexity of the supplier selection problem and the uncertain qualitative factors that are involved in this problem led to the development of techniques that cope with fuzziness by applying fuzzy logic methods [23][24][25][26]. These methods can handle and manipulate fuzziness in a manner that leads to meaningful results.…”

Section: "Buy National" Policies and Lack Of Monitoring Public Procurmentioning

confidence: 99%

Monitoring Public Procurement Using a Fuzzy Logic System

Mardas

Tsadiras²

2015

J Stock Forex Trad

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The problem of monitoring public procurement is a vital issue, especially in the European Union (EU), where the free movement of goods is finally established by the "Single European Act". A monitoring system that could be applied after public procurement contracts have been awarded, would examine and identify the existence both, of corruption and of "buy national" policies and practices (i.e. policies favouring domestic suppliers). In this article, the use of a fuzzy logic system as a monitoring mechanism for public procurement is proposed. Using this system, national or EU surveillance authorities can sort the contractors in a series of categories, identifying the degree of their efficiency. The design and implementation of the proposed fuzzy logic system is presented, followed by demonstrative examples of its operation. This system, which applies mainly to goods and services, can also be used as a decision support system at the stage of the selection process, assisting the choice of the best contractor.

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“…Several types of integrated QFD technique [41] have been used in determining as well as ranking candidate supplier. Researchers are proposed the introduction of Fuzzy technique [42] for selection of processes.…”

Section: Related Workmentioning

confidence: 99%

A Novel Integrated AHP-QFD Model for Software Project Selection under Fuzziness

Bakshi¹,

Sarkar²,

Sanyal³

2012

IJCA

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Now-a-days software manufacturing companies usually try to capture market share with rapid software development. Actually the development of high quality software products can decrease cost by reducing rework and increasing productivity. For that, reason selection of software projects is an important task. Several factors come into consideration while selection of proper project for a specified job. To deal with this typical situation the current researchers combined the much known AHP(Analytic Hierarchy Process) with QFD (Quality Function Deployment). Here the AHP method redefined under fuzziness. Then QFD process is applied to identifying and ranking customer's need and translating them into product / service specification. At the last sensitivity analysis has been done to make the process more robust from the characterization of integration of the fuzzy AHP & QFD.

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A fuzzy-QFD approach to supplier selection

Cited by 332 publications

References 60 publications

A fuzzy MADM approach for project selection: a six sigma case study

A fuzzy MADM approach for project selection: a six sigma case study

Monitoring Public Procurement Using a Fuzzy Logic System

A Novel Integrated AHP-QFD Model for Software Project Selection under Fuzziness

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