Representação de percepções de consumidores : o emprego da Engenharia Kansei para a construção de painéis semânticos

• Ano de defesa: 2017
• Autor(a) principal: Zabotto, Cristina Nardin
• Orientador(a): Silva, Sérgio Luis da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• Palavras-chave em Português: Engenharia Kansei; Painel semântico; Desenvolvimento de produto
• Palavras-chave em Inglês: Design; Mood board; Rough set; Kansei Engineering; Product development
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::ENGENHARIA DO PRODUTO::DESENVOLVIMENTO DE PRODUTO
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/9722

The research introduces an algorithm based on the Kansei Engineering System capable of producing Semantic Panels for the use of professionals during product development. Semantic Panels are comprised of a series of visual images used by designers to express the emotions of potential customers, supporting the analysis of creative ideas for product development. The Kansei Engineering system has the role of linking consumers’ feelings and emotions to product descriptive features. By developing and algorithm when these two pieces of information are linked to each other, and by identifying the existing interactions by means of Rough Set statistical analysis, professionals enrich the material available for decision making. By comparing it with the existing literature, this is a new formulation for the use of the Kansei Engineering System for production of Semantic Panels structured into five cycles, and capturing users’ opinions in all stages of the creation process. The above-mentioned algorithm was developed and a subset of real data was used for applying the procedure to a product of consumer goods. The proposal was proven a feasible alternative for the construction of Semantic Panels based on consumers’ information.