DOI : https://doi.org/10.18517/ijaseit.12.3.16091

Decision Method Focused on the Fuzzy Front-End Phase: A Study Applied to the Development of an Electronic Starting Block for Running Athletes

Ana Caroline Dzulinski (1), Aldo Braghini Junior (2), Lucas Medeiros Souza do Nascimento (3), Daiane Maria de Genaro Chiroli (4), Sergio Luiz Stevan Junior (5), João Carlos Colmenero (6)
(1) Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS), campus Caxias do Sul, Avelino Antônio de Souza, 1730, Nossa Sra. de Fátima, Caxias do Sul, RS, 95043-700, Brasil
(2) Universidade Tecnológica Federal do Paraná (UTFPR), campus Ponta Grossa, Doutor Washington Subtil Chueire, 330, Jardim Carvalho, Ponta Grossa, PR, 84017-220, Brasil
(3) Universidade Tecnológica Federal do Paraná (UTFPR), campus Ponta Grossa, Doutor Washington Subtil Chueire, 330, Jardim Carvalho, Ponta Grossa, PR, 84017-220, Brasil
(4) Universidade Tecnológica Federal do Paraná (UTFPR), campus Apucarana, Marcílio Dias, 635, Jardim Paraiso, Apucarana, PR, 86812-460, Brasil.
(5) Universidade Tecnológica Federal do Paraná (UTFPR), campus Ponta Grossa, Doutor Washington Subtil Chueire, 330, Jardim Carvalho, Ponta Grossa, PR, 84017-220, Brasil
(6) Universidade Tecnológica Federal do Paraná (UTFPR), campus Ponta Grossa, Doutor Washington Subtil Chueire, 330, Jardim Carvalho, Ponta Grossa, PR, 84017-220, Brasil
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How to cite (IJASEIT) :
Dzulinski, Ana Caroline, et al. “Decision Method Focused on the Fuzzy Front-End Phase: A Study Applied to the Development of an Electronic Starting Block for Running Athletes”. International Journal on Advanced Science, Engineering and Information Technology, vol. 12, no. 3, June 2022, pp. 1253-62, doi:10.18517/ijaseit.12.3.16091.
Citation Format :
In this work, we present a model to support multi-criteria decision-making in the selection of components for the initial proposals of a product or portfolio of products during the Fuzzy Front-End (FFE) phase of the Product Development Process (PD) to reduce risk and uncertainty and increase agility. The model is made of eight stages in which triangular-based fuzzy is employed to weigh customer requirements, and a direct numerical scale is used to weigh technical requirements. The main differences of this model are the identification and weighting of requirements based on different customer profiles and the identification of global customer requirements that have a direct or indirect relationship with all or most technical requirements. We applied the model in the development of an electronic starting block for running athletes with sensors that collected data to assist in training and performance improvement and were able to reduce the number of combinations of components in the FFE stage, and consequently, the development time, with the prioritization of roughly 30% of the components (10 parts of a total of 33). We highlight that there is still a need for further studies investigating the relationship of customer profiles and the impact on PDP and other ways to analyze how customer requirements impact technical requirements.

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