Proposição de um modelo hesitant fuzzy QFD para seleção de fornecedores em projetos

• Ano de defesa: 2019
• Autor(a) principal: Siqueira Júnior, José Antonio
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Administração; UTFPR
• Palavras-chave em Português: Administração de projetos; Conjuntos difusos; Desdobramento da função qualidade; Departamentos de compras; Métodos de simulação; Processo decisório por critério múltiplo; Administração; Project management; Fuzzy sets; Quality function deployment; Purchasing departments; Simulation methods; Multiple criteria decision making; Management; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO::PESQUISA OPERACIONAL
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/4270

The option to contract products or services brings great changes to the project environment, due to the influence that the suppliers' performance has on the result of the project. It contributes to generate a critical activity to the project scope and, consequently, to the expected results: the selection of suppliers. Assuming that the choice of the correct supplier for the project requires the adoption of a method able to consider a large variety of criteria, this study proposed a decision model based on hesitant fuzzy linguistic term sets with QFD (Quality Function Deployment) technique. Although the application of this technique can bring several benefits to the decisionmaking process, the literature does not present previous studies that propose decision models for supplier selection based on hesitant fuzzy QFD. This study adopts an empirical descriptive quantitative approach, based on modeling and simulation, the computational implementation of this model was done using MS Excel. A pilot application was performed in order to select a supplier for a project of an energy sector company. Three suppliers were evaluated by three professionals of the organization, which scored the alternatives according to the requirements and criteria defined by themselves. The results of the application suggest the effectiveness of the model. In addition, results of the sensitivity analysis reinforces the adequacy of the developed model. The proposed presents benefits such as support to the selection stage of criteria considering the difficulty of data collection, as well as the possibility of using linguistic expressions and to incorporate a pessimistic or optimistic view to the decision making process.