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, Aldo Braghini Junior, Lucas Medeiros Souza do Nascimento, Daiane Maria de Genaro Chiroli, Sergio Luiz Stevan Junior, João Carlos Colmenero

Abstract


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.

Keywords


Product development; fuzzy-front end; customer requirements; decision method; electronic starting block.

Full Text:

PDF

References


R. G. Cooper, “Perspective: The stage-gates® idea-to-launch process - Update, what’s new, and NexGen systems,†Journal of Product Innovation Management, vol. 25, no. 3, pp. 213–232, 2008, doi: 10.1111/j.1540-5885.2008.00296.x.

K. T. Ulrich and S. D. Eppinger, Product design and development., 5th ed. New York: McGraw-Hill, 2012.

C. M. Crawford and C. A. DiBenedetto, New products management, 10th ed. McGraw-Hill, 2010.

N. Iheanachor, I. O. Umukoro, and O. David-West, “The role of product development practices on new product performance: Evidence from Nigeria’s financial services providers,†Technological Forecasting and Social Change, vol. 164, 2021, doi: 10.1016/j.techfore.2020.120470.

C. Relvas and A. Ramos, “New methodology for product development process using structured tools,†Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 235, no. 3, pp. 378–393, 2021, doi: 10.1177/0954405420971228.

J. Oh, J. Yang, and S. Lee, “Managing uncertainty to improve decision-making in NPD portfolio management with a fuzzy expert system,†Expert Systems with Applications, vol. 39, no. 10, pp. 9868–9885, 2012, doi: 10.1016/j.eswa.2012.02.164.

P. G. Smith and D. G. Reinertsen, Developing products in half the time. New York: Van Nostrand Reinhold, 1991.

C. L. K. Yamamura, C. O. Ribeiro, D. Dantas, J. A. Quintanilha, and F. T. Berssaneti, “The front-end of product development as systems thinking and predictive learning,†in Procedia Manufacturing, 2019, vol. 39, pp. 1346–1353. doi: 10.1016/j.promfg.2020.01.323.

D. Park, J. Han, and P. R. N. Childs, “266 Fuzzy front-end studies: current state and future directions for new product development,†Research in Engineering Design, vol. 32, no. 3, pp. 377–409, 2021, doi: 10.1007/s00163-021-00365-w.

A. Bhatia, J. Cheng, S. Salek, V. Chokshi, and A. Jetter, “Improving the effectiveness of fuzzy front end management: Expanding stage-gate methodologies through agile,†in PICMET 2017 - Portland International Conference on Management of Engineering and Technology: Technology Management for the Interconnected World, Proceedings, 2017, vol. 2017-Janua, pp. 1–8. doi: 10.23919/PICMET.2017.8125390.

A. Albers, J. Reinemann, T. Hirschter, J. Fahl, and N. Heitger, “Validation-driven design in the early phase of product development,†in Procedia CIRP, 2019, vol. 84, pp. 630–637. doi: 10.1016/j.procir.2019.04.211.

E. Kern et al., “Sustainable software products—Towards assessment criteria for resource and energy efficiency,†Future Generation Computer Systems, vol. 86, pp. 199–210, 2018, doi: 10.1016/j.future.2018.02.044.

R. G. Cooper, “The drivers of success in new-product development,†Industrial Marketing Management, vol. 76, pp. 36–47, 2019, doi: 10.1016/j.indmarman.2018.07.005.

T. Morgan, M. Obal, and S. Anokhin, “Customer participation and new product performance: Towards the understanding of the mechanisms and key contingencies,†Research Policy, vol. 47, no. 2, pp. 498–510, 2018, doi: 10.1016/j.respol.2018.01.005.

M. Vaquero Martín, “Communicating new product development openness – The impact on consumer perceptions and intentions,†European Management Journal, 2021, doi: 10.1016/j.emj.2021.01.004.

A. Sihvonen and K. Pajunen, “Causal complexity of new product development processes: a mechanism-based approach,†Innovation: Organization and Management, vol. 21, no. 2, pp. 253–273, 2019, doi: 10.1080/14479338.2018.1513333.

X. Zhang and V. Thomson, “Modelling the development of complex products using a knowledge perspective,†Research in Engineering Design, vol. 30, no. 2, pp. 203–226, 2019, doi: 10.1007/s00163-017-0274-3.

R. D. S. Bolaños and S. C. M. Barbalho, “Exploring product complexity and prototype lead-times to predict new product development cycle-times,†International Journal of Production Economics, vol. 235, 2021, doi: 10.1016/j.ijpe.2021.108077.

J. Yang, D. Tang, S. Li, Q. Wang, and H. Zhu, “An improved iterative stochastic multi-objective acceptability analysis method for robust alternative selection in new product development,†Advanced Engineering Informatics, vol. 43, 2020, doi: 10.1016/j.aei.2020.101038.

S. A. Mousavi, H. Seiti, A. Hafezalkotob, S. Asian, and R. Mobarra, “Application of risk-based fuzzy decision support systems in new product development: An R-VIKOR approach,†Applied Soft Computing, vol. 109, 2021, doi: 10.1016/j.asoc.2021.107456.

M. Relich and P. Pawlewski, “A fuzzy weighted average approach for selecting portfolio of new product development projects,†Neurocomputing, vol. 231, pp. 19–27, 2017, doi: 10.1016/j.neucom.2016.05.104.

C.-S. Ying, Y.-L. Li, K.-S. Chin, H.-T. Yang, and J. Xu, “A new product development concept selection approach based on cumulative prospect theory and hybrid-information MADM,†Computers and Industrial Engineering, vol. 122, pp. 251–261, 2018, doi: 10.1016/j.cie.2018.05.023.

A. Liu, H. Hu, X. Zhang, and D. Lei, “Novel Two-Phase Approach for Process Optimization of Customer Collaborative Design Based on Fuzzy-QFD and DSM,†IEEE Transactions on Engineering Management, vol. 64, no. 2, pp. 193–207, 2017, doi: 10.1109/TEM.2017.2651052.

C. Kahraman, F. K. Gündoğdu, A. Karaşan, and E. Boltürk, Advanced Fuzzy Sets and Multicriteria Decision Making on Product Development, vol. 279. 2020. doi: 10.1007/978-3-030-42188-5_15.

W.-C. Chen, Y.-F. Lin, K.-P. Liu, H.-P. Chang, L.-Y. Wang, and P.-H. Tai, “A Complete MCDM Model for NPD Performance Assessment in an LED-Based Lighting Plant Factory,†Mathematical Problems in Engineering, vol. 2018, 2018, doi: 10.1155/2018/7049208.

M. Khastehdel and S. Mansour, “Developing a dynamic model for idea selection during fuzzy front end of innovation,†in 2018 7th International Conference on Industrial Technology and Management, ICITM 2018, 2018, vol. 2018-Janua, pp. 78–82. doi: 10.1109/ICITM.2018.8333923.

O. Sankowski et al., “Challenges in early phase of product family development processes,†in Procedia CIRP, 2021, vol. 100, pp. 840–845. doi: 10.1016/j.procir.2021.05.034.

L. C. Cheng and Leonel Del Rey de Melo Filho, QFD: desdobramento da função qualidade na gestão de desenvolvimento de produtos. Editora Blucher, 2007.

S. Milunovic Koprivica and J. Filipovic, “Application of Traditional and Fuzzy Quality Function Deployment in the Product Development Process,†EMJ - Engineering Management Journal, vol. 30, no. 2, pp. 98–107, 2018, doi: 10.1080/10429247.2018.1438027.

A. Fetanat and M. Tayebi, “Sustainable design of the household water treatment systems using a novel integrated fuzzy QFD and LINMAP approach: a case study of Iran,†Environment, Development and Sustainability, vol. 23, no. 10, pp. 15031–15061, 2021, doi: 10.1007/s10668-021-01284-5.

S. M. Li, F. T. S. Chan, Y. P. Tsang, and H. Y. Lam, “New product idea selection in the fuzzy front end of innovation: A fuzzy best-worst method and group decision-making process,†Mathematics, vol. 9, no. 4, pp. 1–18, 2021, doi: 10.3390/math9040337.

H. Lüuthen et al., Finding the best: Mathematical optimization based on product and process requirements. 2017. doi: 10.1007/978-3-319-52377-4_5.

T. Keiningham et al., “Customer experience driven business model innovation,†Journal of Business Research, vol. 116, pp. 431–440, 2020, doi: 10.1016/j.jbusres.2019.08.003.

H. Kärkkäinen, P. Piippo, and M. Tuominen, “Ten tools for customer-driven product development in industrial companies,†International Journal of Production Economics, vol. 69, no. 2, pp. 161–176, 2001, doi: 10.1016/S0925-5273(00)00030-X.

J. Zhang, A. Simeone, P. Gu, and B. Hong, “Product features characterization and customers’ preferences prediction based on purchasing data,†CIRP Annals, vol. 67, no. 1, pp. 149–152, 2018, doi: 10.1016/j.cirp.2018.04.020.

J. Xie, Q. Qin, and M. Jiang, “Multiobjective Decision-Making for Technical Characteristics Selection in a House of Quality,†Mathematical Problems in Engineering, vol. 2020, 2020, doi: 10.1155/2020/9243142.

Y.-J. Wang, “A fuzzy multi-criteria decision-making model based on simple additive weighting method and relative preference relation,†Applied Soft Computing Journal, vol. 30, pp. 412–420, 2015, doi: 10.1016/j.asoc.2015.02.002.

F. C. Zola, J. C. Colmenero, F. V. Aragão, T. Rodrigues, and A. B. Junior, “Multicriterial model for selecting a charcoal kiln,†Energy, vol. 190, 2020, doi: 10.1016/j.energy.2019.116377.

M. Alemi-Ardakani, A. S. Milani, S. Yannacopoulos, and G. Shokouhi, “On the effect of subjective, objective and combinative weighting in multiple criteria decision making: A case study on impact optimization of composites,†Expert Systems with Applications, vol. 46, pp. 426–438, 2016, doi: 10.1016/j.eswa.2015.11.003.

Kistler Group., “Blocks Multicomponent Force Measurement for Sprint Starts. ,†https://www.kistler.com/?type=669&fid=40548&model=document. , Jan. 2020.




DOI: http://dx.doi.org/10.18517/ijaseit.12.3.16091

Refbacks

  • There are currently no refbacks.


Published by INSIGHT - Indonesian Society for Knowledge and Human Development