Skip to main content
SpringerLink
Log in

Heterogeneous Information Integrated QFD for Smart Bicycle Design

  • Chapter
  • First Online:
Customer Oriented Product Design

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 279))

  • 913 Accesses

Abstract

The developing technology started to define a new set of functions and potentials for the products. Customers that keep up with the developing technologies expect to experience cutting-edge technologies in their products. Amid these expectations, the market has become a very competitive place where everybody wants to strike the customer’s attention with high technology. On the other hand, non-customer oriented high technology often intimidates end-users, and that decreases the preferability of the product. Motivated by the critical importance of customer-oriented design, this contribution presents a smart product design methodology with heterogeneous information. The non-homogeneity of the information comes from its variant decision-making group as the potential customers and experts. Quality Function Deployment (QFD), which is a very well known, powerful tool for product design is chosen for this methodology. House of Quality (HoQ) of QFD is extended with the 2-Tuple linguistic model to create a flexible environment for decision makers (DMs). Furthermore, multi-preference relations technique is used to handle heterogeneous information while calculating the customer requirements’ importance. A case study about the smart bicycle design is presented with the results to test the plausibility of the suggested methodology at the end of the contribution.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Xu, Y., Chen, G., Zheng, J.: An integrated solution—KAGFM for mass customization in customer-oriented product design under cloud manufacturing environment. Int. J. Adv. Manuf. Technol. 84, 85–101 (2016). https://doi.org/10.1007/s00170-015-8074-2

    Article  Google Scholar 

  2. Akao, Y.: An Introduction to Quality Function Deployment. Productivity Press, Cambridge, Massachusetts (1990)

    Google Scholar 

  3. Martínez, L., Rodriguez, R.M., Herrera, F.: The 2-tuple Linguistic Model. Springer International Publishing, Cham (2015)

    Book  Google Scholar 

  4. Büyüközkan, G., Güleryüz, S.: Extending fuzzy QFD methodology with GDM approaches: an application for IT planning in collaborative product development. Int. J. Fuzzy Syst. 17, 544–558 (2015). https://doi.org/10.1007/s40815-015-0065-9

    Article  Google Scholar 

  5. Büyüközkan, G., Ilıcak, Ö.: Integrated SWOT analysis with multiple preference relations: selection of strategic factors for social media. Kybernetes 48, 451–470 (2019)

    Article  Google Scholar 

  6. Iranmanesh, H., Tabrizi, B.H.: An integrated framework for customer-oriented web design using QFD, Kano model and ANP. In: 2009 International Conference on Computers & Industrial Engineering, pp. 1674–1679. IEEE, Troyes, France (2009)

    Google Scholar 

  7. Chen, L.-H., Ko, W.-C.: Fuzzy linear programming models for new product design using QFD with FMEA. Appl. Math. Model. 33, 633–647 (2009). https://doi.org/10.1016/j.apm.2007.11.029

    Article  MATH  Google Scholar 

  8. Lee, A.H.I., Lin, C.-Y.: An integrated fuzzy QFD framework for new product development. Flex. Serv. Manuf. J. 23, 26–47 (2011). https://doi.org/10.1007/s10696-011-9076-5

    Article  MATH  Google Scholar 

  9. Camgoz-Akdag, H., Zaim, S., Acar, M.F., et al.: Product improvement with quality function deployment (QFD) technique. Adv. Mater. Res. 445, 1058–1063 (2012). https://doi.org/10.4028/www.scientific.net/AMR.445.1058

    Article  Google Scholar 

  10. Wang, C.-H., Chen, J.-N.: Using quality function deployment for collaborative product design and optimal selection of module mix. Comput. Ind. Eng. 63, 1030–1037 (2012). https://doi.org/10.1016/j.cie.2012.06.014

    Article  Google Scholar 

  11. Chen, L.-H., Ko, W.-C., Tseng, C.-Y.: Fuzzy approaches for constructing house of quality in QFD and its applications: a group decision-making method. IEEE Trans. Eng. Manag. 60, 77–87 (2013). https://doi.org/10.1109/TEM.2012.2204063

    Article  Google Scholar 

  12. Yuen, K.K.F.: A hybrid fuzzy quality function deployment framework using cognitive network process and aggregative grading clustering: an application to cloud software product development. Neurocomputing 142, 95–106 (2014). https://doi.org/10.1016/j.neucom.2014.03.045

    Article  Google Scholar 

  13. Ionica, A.C., Leba, M.: QFD integrated in new product development—biometric identification system case study. Procedia Econ. Finance 23, 986–991 (2015). https://doi.org/10.1016/S2212-5671(15)00454-2

    Article  Google Scholar 

  14. Aghdam, M.M., Mahdavi, I., Shirazi, B., Vahidi, J.: House of quality improvement by new design requirements generation. In: 2015 International Conference on Industrial Engineering and Operations Management (IEOM), pp 1–9. IEEE, Dubai (2015)

    Google Scholar 

  15. Lin, C.-Y., Lee, A.H.I., Kang, H.-Y.: An integrated new product development framework—an application on green and low-carbon products. Int. J. Syst. Sci. 46, 733–753 (2015). https://doi.org/10.1080/00207721.2013.798447

    Article  Google Scholar 

  16. Zheng, P., Xu, X., Xie, S.Q.: A weighted preference graph approach to analyze incomplete customer preference information in QFD product planning. In: 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp 1070–1074. IEEE, Bali, Indonesia (2016)

    Google Scholar 

  17. Liu, A., Hu, H., Zhang, X., Lei, D.: Novel two-phase approach for process optimization of customer collaborative design based on fuzzy-QFD and DSM. IEEE Trans. Eng. Manag. 64, 193–207 (2017). https://doi.org/10.1109/TEM.2017.2651052

    Article  Google Scholar 

  18. Ahmadabadi, H.Z., Zamzam, F., Meybodi, F.R. et al.: Development of a new sesame product using QFD and DOE methods: a case study of sesame product in yazd. Montenegrin J. Econ. 14, 27–44 (2018). https://doi.org/10.14254/1800-5845/2018.14-1.2

  19. Dursun, M., Arslan, Ö.: An integrated decision framework for material selection procedure: a case study in a detergent manufacturer. Symmetry 10, 657 (2018). https://doi.org/10.3390/sym10110657

    Article  MATH  Google Scholar 

  20. Alptekin, S.E., Alptekin, G.I.: A fuzzy quality function deployment approach for differentiating cloud products. Int. J. Comput. Intell. Syst. 11, 1041 (2018). https://doi.org/10.2991/ijcis.11.1.79

    Article  Google Scholar 

  21. Huang, J., You, X.-Y., Liu, H.-C., Si, S.-L.: New approach for quality function deployment based on proportional hesitant fuzzy linguistic term sets and prospect theory. Int. J. Prod. Res. 57, 1283–1299 (2019). https://doi.org/10.1080/00207543.2018.1470343

    Article  Google Scholar 

  22. Zhang, X.: User selection for collaboration in product development based on QFD and DEA approach. J. Intell. Manuf. 30, 2231–2243 (2019). https://doi.org/10.1007/s10845-017-1386-3

    Article  Google Scholar 

  23. Büyüközkan, G., Feyzioğlu, O.: Group decision making to better respond customer needs in software development. Comput. Ind. Eng. 48, 427–441 (2005)

    Article  Google Scholar 

  24. Büyüközkan, G., Feyzioğlu, O., Ruan, D.: Fuzzy group decision-making to multiple preference formats in quality function deployment. Comput. Ind. 58, 392–402 (2007)

    Article  Google Scholar 

  25. Li, Y.-L., Tang, J.-F., Chin, K.-S., et al.: On integrating multiple type preferences into competitive analyses of customer requirements in product planning. Int. J. Prod. Econ. 139, 168–179 (2012). https://doi.org/10.1016/j.ijpe.2012.03.031

    Article  Google Scholar 

  26. Wang, Y., Zhang, Z., Koh, C.-K., et al.: Passivity enforcement for descriptor systems via matrix pencil perturbation. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 31, 532–545 (2012)

    Article  Google Scholar 

  27. Büyüközkan, G., Çifçi, G.: An integrated QFD framework with multiple formatted and incomplete preferences: a sustainable supply chain application. Appl. Soft Comput. 13, 3931–3941 (2013)

    Article  Google Scholar 

  28. Büyüközkan, G., Çifçi, G.: An extended quality function deployment incorporating fuzzy logic and GDM under different preference structures. Int. J. Comput. Intell. Syst. 8, 438–454 (2015). https://doi.org/10.1080/18756891.2015.1017379

    Article  Google Scholar 

  29. Li, Z., Gao, Q., Zhang, D., Liu, G.: A New Method of Rating the Importance of Customer Needs in Quality Function Deployment. IEEE, New York (2008)

    Google Scholar 

  30. Dursun, M., Karsak, E.E.: Supplier selection using an integrated decision making approach based on QFD and 2-tuple fuzzy representation. World Congress on Engineering and Computer Science, WCECS 2012, vol. Ii, pp. 1309–1315. Int Assoc Engineers-Iaeng, Hong Kong (2012)

    Google Scholar 

  31. Li, M.: The extension of quality function deployment based on 2-tuple linguistic representation model for product design under multigranularity linguistic environment. Math. Probl. Eng. 989284. (2012). https://doi.org/10.1155/2012/989284

    Google Scholar 

  32. Wang, S.-Y.: Applying the superior identification group linguistic variable to construct kano model oriented quality function deployment. Technol. Econ. Dev. Econ. 19, S304–S325 (2013). https://doi.org/10.3846/20294913.2013.880082

    Article  Google Scholar 

  33. Ai, Q., Shu, T., Liu, Q., et al.: A method for determining customer requirement weights based on TFMF and TLR. Enterp. Inf. Syst. 7, 569–580 (2013). https://doi.org/10.1080/17517575.2012.763190

    Article  Google Scholar 

  34. Mi, C., Qiang, Y., Liu, S., et al.: An integrated failure prioritizing model of complex equipment. J. Grey. Syst. 27, 39–50 (2015)

    Google Scholar 

  35. Karsak, E.E., Dursun, M.: An integrated fuzzy MCDM approach for supplier evaluation and selection. Comput. Ind. Eng. 82, 82–93 (2015). https://doi.org/10.1016/j.cie.2015.01.019

    Article  Google Scholar 

  36. Sheng, Z., Yan, L.: The quality function deployment and 2-tuple linguistic based approach to third party logistics supplier selection. Sichuan Univ Press, Chengdu (2016)

    Google Scholar 

  37. Wang, Z.-L., You, J.-X., Liu, H.-C.: Uncertain quality function deployment using a hybrid group decision making model. Symmetry-Basel 8, 119 (2016). https://doi.org/10.3390/sym8110119

    Article  MathSciNet  Google Scholar 

  38. Li, X., He, Z.: Determining importance ratings of patients’ requirements with multi-granular linguistic evaluation information. Int. J. Prod. Res. 55, 4110–4122 (2017). https://doi.org/10.1080/00207543.2016.1253890

    Article  Google Scholar 

  39. Buyukozkan, G., Uzturk, D.: Combined QFD TOPSIS approach with 2-tuple linguistic information for warehouse selection. In: 2017 IEEE International Conference on Fuzzy Systems (Fuzz-IEEE). IEEE, New York (2017)

    Google Scholar 

  40. Liu, M., Gao, Q.: Supplier evaluation in TSC based on fuzzy linguistic term sets and QFD. In: 2017 29th Chinese Control and Decision Conference (CCDC), pp 4671–4675. IEEE, New York (2017)

    Google Scholar 

  41. He, L., Ming, X., Li, M., et al.: Understanding customer requirements through quantitative analysis of an improved fuzzy Kano’s model. Proc. Inst. Mech. Eng., Part B: J. Eng. Manuf. 231, 699–712 (2017). https://doi.org/10.1177/0954405415598894

    Article  Google Scholar 

  42. Zhang, X., Su, J.: An integrated QFD and 2-tuple linguistic method for solution selection in crowdsourcing contests for innovative tasks. J. Intell. Fuzzy Syst. 35, 6329–6342 (2018). https://doi.org/10.3233/JIFS-181122

    Article  Google Scholar 

  43. Mei, Y., Liang, Y., Tu, Y.: A multi-granularity 2-tuple QFD method and application to emergency routes evaluation. Symmetry-Basel 10, 484 (2018). https://doi.org/10.3390/sym10100484

    Article  Google Scholar 

  44. Mi, C., Chen, Y., Zhou, Z., Lin, C.-T.: Product redesign evaluation: An improved quality function deployment model based on failure modes and effects analysis and 2-tuple linguistic. Adv. Mech. Eng. 10, 1687814018811227 (2018). https://doi.org/10.1177/1687814018811227

    Article  Google Scholar 

  45. Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans. Fuzzy Syst. 8, 746–752 (2000)

    Article  Google Scholar 

  46. Akao, Y., Mazur, G.H.: The leading edge in QFD: past, present and future. Int. J. Qual. Reliab. Manag. 20, 20–35 (2003)

    Article  Google Scholar 

  47. Akao, Y.: QFD: integrating customer requirements into product design. Camb MA (1990)

    Google Scholar 

  48. Zhang, B., Dong, Y., Xu, Y.: Maximum expert consensus models with linear cost function and aggregation operators. Comput. Ind. Eng. 66, 147–157 (2013). https://doi.org/10.1016/j.cie.2013.06.001

    Article  Google Scholar 

  49. Xia, M., Xu, Z., Chen, N.: Some hesitant fuzzy aggregation operators with their application in group decision making. Group Decis. Negot. 22, 259–279 (2013). https://doi.org/10.1007/s10726-011-9261-7

    Article  Google Scholar 

  50. Herrera, F., Herrera-Viedma, E., Chiclana, F.: Multiperson decision-making based on multiplicative preference relations. Eur. J. Oper. Res. 129, 372–385 (2001). https://doi.org/10.1016/S0377-2217(99)00197-6

    Article  MathSciNet  MATH  Google Scholar 

  51. Herrera, F., Herrera-Viedma, E., Martı́nez, L.: A fusion approach for managing multi-granularity linguistic term sets in decision making. Fuzzy Sets Syst. 114, 43–58 (2000). https://doi.org/10.1016/S0165-0114(98)00093-1

Download references

Acknowledgements

The authors would like to thank the industrial experts for their support, as well as acknowledge the grants of Galatasaray University Research Fund (Projects Numbers: 19.402.001, 19.402.003 and 19.402.006).

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Galatasaray University, 34349, Istanbul, Turkey

    Gülçin Büyüközkan & Öykü Ilıcak

  2. Department of Management, Galatasaray University, 34349, Istanbul, Turkey

    Deniz Uztürk

Authors
  1. Gülçin Büyüközkan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Deniz Uztürk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Öykü Ilıcak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gülçin Büyüközkan .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Faculty of Management, Istanbul Technical University, Macka, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Faculty of Mechanical Engineering, Yildiz Technical University, Besiktas, Istanbul, Turkey

    Selcuk Cebi

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Büyüközkan, G., Uztürk, D., Ilıcak, Ö. (2020). Heterogeneous Information Integrated QFD for Smart Bicycle Design. In: Kahraman, C., Cebi, S. (eds) Customer Oriented Product Design. Studies in Systems, Decision and Control, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-030-42188-5_7

Download citation

Publish with us

Policies and ethics

Search

Navigation