A carregar...
Publicação
Seleção de fornecedores na gestão de compras da manutenção - estudo de caso numa indústria de papel
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.66 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Num contexto empresarial cada vez mais competitivo, a área de compras tem assumido um papel estratégico fundamental, especialmente no que se refere à seleção de fornecedores. Esta dissertação aborda a importância de um departamento de compras bem estruturado, focado na criação de parcerias sólidas, seleção de fornecedores e na otimização de custos, uma vez que o futuro das organizações vai depender cada vez mais deste departamento para responder às necessidades do cliente e do mercado. O processo de seleção de fornecedores, anteriormente baseado apenas em critérios simples como o custo, evoluiu para um modelo multicritério que considera dimensões tanto qualitativas quanto quantitativas.
A presente dissertação tem como objetivo aplicar e comparar dois métodos multicritério de apoio à decisão – Fuzzy-TOPSIS e PROMETHEE – no contexto da seleção de fornecedores para a área de compras de manutenção numa indústria de papel. O trabalho parte da identificação dos critérios mais relevantes para o processo de decisão, como o preço, o lead time, os custos de transporte, o cumprimento dos prazos de entrega e o serviço pós-venda. Com base na perceção de um decisor interno, são atribuídas ponderações aos critérios e avaliações linguísticas aos fornecedores, posteriormente convertidas em representações numéricas fuzzy.
O método Fuzzy-TOPSIS permitiu captar a subjetividade e a incerteza nas avaliações qualitativas, transformando-as em índices de proximidade às soluções ideais. Já o método PROMETHEE, com os seus fluxos de preferência positivos e negativos e ferramentas como o GAIA Plane, possibilitou uma análise gráfica das alternativas e dos conflitos entre critérios. Ambos os métodos revelaram o Fornecedor C como a melhor alternativa, embora com diferenças nos rankings intermédios das demais alternativas, devido à influência das estruturas algorítmicas próprias de cada abordagem.
Adicionalmente, foi realizada uma análise de sensibilidade com recurso ao gráfico Walking Weight do PROMETHEE, que demonstrou a robustez do Fornecedor C mesmo perante variações significativas nos pesos dos critérios. Em contrapartida, os fornecedores A, B e D mostraram maior instabilidade nas suas posições, dependendo das prioridades estratégicas consideradas.
Os resultados desta dissertação evidenciam que a aplicação de métodos multicritério à seleção de fornecedores proporciona maior rigor, transparência e fundamentação ao processo de tomada de decisão. A comparação entre os métodos reforça a importância de uma abordagem plural e adaptável, contribuindo para decisões mais alinhadas com os objetivos e restrições da empresa.
In an increasingly competitive business environment, purchasing has taken on a key strategic role, especially in terms of supplier selection. This dissertation addresses the importance of a well-structured purchasing department, focused on creating solid partnerships, selecting suppliers and optimizing costs, since the future of organizations will increasingly depend on this department to respond to customer and market needs. The supplier selection process, previously based only on simple criteria such as cost, has evolved into a multi-criteria model that considers both qualitative and quantitative dimensions. The aim of this dissertation is to apply and compare two multi-criteria decision support methods - Fuzzy-TOPSIS and PROMETHEE - in the context of selecting suppliers for the maintenance purchasing area in a paper industry. The work starts by identifying the most relevant criteria for the decision-making process, such as price, lead time, transportation costs, compliance with delivery deadlines and after-sales service. Based on the perception of an internal decision-maker, the criteria are weighted and the suppliers are given linguistic evaluations, which are then converted into fuzzy numerical representations. The Fuzzy-TOPSIS method made it possible to capture subjectivity and uncertainty in qualitative assessments, transforming them into indices of proximity to ideal solutions. The PROMETHEE method, with its positive and negative preference flows and tools such as GAIA Plane, made it possible to graphically analyze the alternatives and the conflicts between criteria. Both methods revealed Supplier C as the best alternative, although there were differences in the intermediate rankings of the other alternatives, due to the influence of the algorithmic structures specific to each approach. In addition, a sensitivity analysis was carried out using PROMETHEE's Walking Weight graph, which demonstrated Supplier C's robustness even in the face of significant variations in the weights of the criteria. On the other hand, suppliers A, B and D showed greater instability in their positions, depending on the strategic priorities considered. The results of this dissertation show that applying multi-criteria methods to supplier selection provides greater rigor, transparency and substantiation to the decision-making process. The comparison between the methods reinforces the importance of a plural and adaptable approach, contributing to decisions that are more in line with the company's objectives and constraints.
In an increasingly competitive business environment, purchasing has taken on a key strategic role, especially in terms of supplier selection. This dissertation addresses the importance of a well-structured purchasing department, focused on creating solid partnerships, selecting suppliers and optimizing costs, since the future of organizations will increasingly depend on this department to respond to customer and market needs. The supplier selection process, previously based only on simple criteria such as cost, has evolved into a multi-criteria model that considers both qualitative and quantitative dimensions. The aim of this dissertation is to apply and compare two multi-criteria decision support methods - Fuzzy-TOPSIS and PROMETHEE - in the context of selecting suppliers for the maintenance purchasing area in a paper industry. The work starts by identifying the most relevant criteria for the decision-making process, such as price, lead time, transportation costs, compliance with delivery deadlines and after-sales service. Based on the perception of an internal decision-maker, the criteria are weighted and the suppliers are given linguistic evaluations, which are then converted into fuzzy numerical representations. The Fuzzy-TOPSIS method made it possible to capture subjectivity and uncertainty in qualitative assessments, transforming them into indices of proximity to ideal solutions. The PROMETHEE method, with its positive and negative preference flows and tools such as GAIA Plane, made it possible to graphically analyze the alternatives and the conflicts between criteria. Both methods revealed Supplier C as the best alternative, although there were differences in the intermediate rankings of the other alternatives, due to the influence of the algorithmic structures specific to each approach. In addition, a sensitivity analysis was carried out using PROMETHEE's Walking Weight graph, which demonstrated Supplier C's robustness even in the face of significant variations in the weights of the criteria. On the other hand, suppliers A, B and D showed greater instability in their positions, depending on the strategic priorities considered. The results of this dissertation show that applying multi-criteria methods to supplier selection provides greater rigor, transparency and substantiation to the decision-making process. The comparison between the methods reinforces the importance of a plural and adaptable approach, contributing to decisions that are more in line with the company's objectives and constraints.
Descrição
Palavras-chave
Gestão de compras Seleção de fornecedores PROMETHEE Fuzzy-TOPSIS Apoio multicritério à decisão Análise de sensibilidade Logística Purchasing Management Supplier Selection Multicriteria Decision Support Sensitivity Analysis Logistics