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- Proposição de um modelo de decisão multicritério para seleção de fornecedores no contexto da indústria 4.0Publication . Resende, Carlos; Geraldes, Carla A.S.; Lima Júnior, Francisco RodriguesA indústria 4.0 compreende a aplicação de diferentes soluções tecnológicas de modo que os processos de negócios em toda a cadeia produtiva sejam integrados. A realização da seleção de fornecedores considerando os requisitos da indústria 4.0 é essencial na promoção de estratégias colaborativas entre fornecedores e fabricantes. Nesse enquadramento, por meio de uma revisão sistemática, foram caracterizados os estudos que propuseram modelos quantitativos para apoiar a seleção de fornecedores no contexto da indústria 4.0. No entanto, não foram encontrados modelos que empreguem critérios de avaliação de fornecedores relacionados a requisitos advindos da indústria 4.0, e que consideram a dificuldade de coletar dados para medir o desempenho dos fornecedores. Assim sendo, a fim de preencher a lacuna de pesquisa identificada, este estudo propõe um modelo de decisão para apoiar a seleção de critérios e fornecedores, com base na combinação de Hesitant Fuzzy Linguistic Term Set (HFLTS) com o método Quality Function Deployment (QFD) considerando um conjunto de critérios definidos a partir de requisitos advindos da indústria 4.0. Para isso, um modelo computacional foi desenvolvido no MS Excel e aplicado em um caso ilustrativo utilizando dados simulados. Por meio dos resultados da aplicação, é possível constatar a capacidade do método em apoiar a tomada de decisão em grupo e considerar pesos diferentes para os julgamentos dos decisores na escolha dos critérios e na avaliação dos fornecedores. A sensibilidade nos parâmetros de saída do modelo às alterações nos parâmetros de entrada sugere efetividade do modelo proposto.
- Decision-making models for formulating and evaluating supplier development programs: a state-of-the-art review and research pathsPublication . Resende, Carlos; Lima-Junior, Francisco Rodrigues; Carpinetti, Luiz Cesar RibeiroSupplier development refers to the efforts of a purchasing company and its suppliers to improve supplier performance and its ability to fulfill the purchasing company’s supply needs. Recently, several quantitative models have appeared in the literature that support decision-making processes regarding supplier development programs (SDPs). To update the latest research related to this subject, as well as contribute towards the establishment of a research agenda, this study presents a review of the literature on decision-making models that assist the formulating and evaluating of SDPs. This review analyzes 65 articles published in relevant journals, which are characterized in terms of several factors which are inherent to decision making in supplier development. The results show that most models focus on formulating SDPs, whereas the most common decision-making methods are Data Envelopment Analysis and Rough Set Theory. The use of multicriteria models and Fuzzy Sets has increased. The research gaps identified allowed us to propose some future research directions on the topic, calling attention to the need of developing new models considering elements that have not yet been studied in the literature, as well as performing comparative studies between them. Our results here can help orient researchers and managers in developing their decision-making processes in terms of SDP formulation and evaluation.
- Decision models for supplier selection in industry 4.0 era: a systematic literature reviewPublication . Resende, Carlos; Geraldes, Carla A.S.; Lima, Francisco RodriguesIndustry 4.0 comprises the application of different technological solutions so that business processes throughout the production chain are integrated. The supplier’s selection, considering the industry 4.0 requirements, is essential in promoting collaborative strategies between suppliers and manufacturers. In this context, this study presents a systematic literature review about quantitative models to support supplier selection in the industry 4.0 era. Fourteen studies were reviewed and characterized in different perspectives such as modelling, application, and validation of the decision model. The results revealed that most of the decision models were developed combining multicriteria decision-making (MCDM) with Artificial Intelligence (AI). Among the criteria related to the Industry 4.0 environment, the most frequent ones were information sharing, technological capacity, digital collaboration and engagement. The gathered results can be useful to guide researchers and managers in the development of computational tools to assist decision-making processes for supplier selection in Industry 4.0 era.