A fuzzy logic approach to supply chain performance management

Ganga, Gilberto Miller Devós; Carpinetti, Luiz César Ribeiro

doi:10.1016/j.ijpe.2011.06.011

Cited by 107 publications

(67 citation statements)

References 25 publications

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“…The subdividing of these metric sets are gave into performance attributes and performance indicators, and a level structure is responsible to a hierarchically sort. Chart 3 describes the composition of the hierarchy by five performance attributes related to reliability, responsiveness, agility, cost and asset management (Ganga & Carpinetti, 2011).…”

Section: The Scormentioning

confidence: 99%

“…Advantage, which is the midpoint performance between the Top 10 business, and the median of all evaluated supply chains. Finally, parity, which is the median of all evaluated supply chain (SCC, 2012;Ganga & Carpinetti, 2011).…”

Section: Author(s) Performance Dimensions Criteriamentioning

confidence: 99%

“…SCOR  also suggests the application of some of its indicators in supplier performance evaluation, as well as in the risk evaluation and benchmarking (SCC, 2012). Anyway, it is noted, analyzing literature studies, that all quantitative SCOR  indicators based methodologies focus to support supply chain performance evaluation (Ganga & Carpinetti, 2011;Agami et al, 2014). …”

Section: Author(s) Performance Dimensions Criteriamentioning

confidence: 99%

“…It was defined three linguistic terms to each input variable and five linguistic terms to each output, based in Altrock (1995) and Lima et al (2014b). Following the study of Ganga & Carpinetti (2011), it was used triangular and trapezoidal fuzzy numbers. Table 1 presents the linguistic terms, the morphologies and the numeric parameters adopted to the pertinence functions modeling of input variables from FIS 1, 2, 3 and 4.…”

Section: Pilot Applicationmentioning

confidence: 99%

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Uma metodologia baseada no modelo SCOR® e em inferência fuzzy para apoiar a avaliação de desempenho de fornecedores

2016

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Resumo: Na literatura acadêmica, tanto a seleção quanto a avaliação para o desenvolvimento de fornecedores vêm sendo abordadas como um problema de tomada de decisão no qual um conjunto de fornecedores é avaliado com base em múltiplos critérios de desempenho. Embora já existam centenas de metodologias quantitativas voltadasAbstract: In the academic literature, supplier selection and evaluation have been addressed as a decision-making problem in which a set of suppliers is assessed based on multiple criteria. Although there are hundreds of quantitative methodologies to support the supplier selection problem, supplier evaluation aiming at developing suppliers is little explored in the literature. Furthermore, most of the existing approaches have some limitations due to the use of inadequate techniques. Thus this study proposes a new methodology to support the assessment of supplier performance, developed from the combination of fuzzy inference systems with some performance indicators of the SCOR  model (Supply Chain Operations Reference). The proposed approach enables the evaluation of aspects related to the performance of operations and costs. The results of this evaluation are used to categorize the suppliers with similar performance and identify guidelines for the management of each supplier group. To demonstrate the modeling process and use, and also to evaluate the suitability of this proposal, a pilot application involving the evaluation of 10 suppliers of a company in the automotive sector was conducted. Four fuzzy inference systems were implemented using MATLAB  and parameterized according to the judgments of two employees of the company. A sensitivity analysis was performed to verify the consistency of the results yielded by these systems. The results support the suitability of the proposed methodology and the parameterization performed during implementation. When compared with the methodologies for the assessment of suppliers in the literature, this approach presents advantages such as the appointment of guidelines for the management of the supplier base; the possibility of integration with the supply chain performance evaluation; the ability to assess simultaneously a non-limited amount of suppliers, the representation and processing of information in a linguistic format, and the mapping and internal storage of all decision scenarios of the problem.

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Section: The Scormentioning

confidence: 99%

Section: Author(s) Performance Dimensions Criteriamentioning

confidence: 99%

Section: Author(s) Performance Dimensions Criteriamentioning

confidence: 99%

Section: Pilot Applicationmentioning

confidence: 99%

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Uma metodologia baseada no modelo SCOR® e em inferência fuzzy para apoiar a avaliação de desempenho de fornecedores

2016

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show abstract

“…However, this model has a limitation to address a wide range of cost structures that a buyer can possibly have. Ganga and Carpinetti (2011) and Costantino et al (2012) proposed some valuable supply chain models in fuzzy environment. Sinha and Sarmah (2008) extended their work considering quantity discount policy.…”

Section: Introductionmentioning

confidence: 99%