Skip to main content
Log in

Quality function deployment improvement: A bibliometric analysis and literature review

  • Published:
Quality & Quantity Aims and scope Submit manuscript

Abstract

Quality function deployment (QFD) is a customer-driven product development tool used to convert customer requirements into engineering characteristics to maximize customer satisfaction. In real applications, however, the traditional QFD method has been criticized as having lots of deficiencies. Over the past decades, many models and approaches have been suggested for improving QFD, but a paucity of contributions are devoted to review and summarize the related researches on the basis of bibliometric analysis. In this paper, we conduct a comprehensive bibliometric analysis of the journal articles on QFD improvement during the years of 1999–2020. First, the metadata analysis of identified articles was presented to clarify the research progress and development trend in this field. Then, bibliometric analyses of the selected articles are conducted to identify the most prolific and influential researchers, the most productive institutions and their collaborations, and the intellectual structure of studies in QFD development. Via keyword analysis, the research focuses and emerging research trends for QFD improvement are found out. Finally, blind spots and future research directions in the area are summarized to provide valuable reference for the future research of QFD advancement.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Akao, Y.: New product development and quality assurancequality deployment system. Stand. Qual. Control 25(4), 7–14 (1972)

    Google Scholar 

  • Akao, Y., Mazur, G.H.: The leading edge in QFD: Past, present and future. Int. J. Qualit. Reliab. Manag. 20(1), 20–35 (2003)

    Article  Google Scholar 

  • Akkawuttiwanich, P., Yenradee, P.: Fuzzy QFD approach for managing SCOR performance indicators. Comput. Ind. Eng. 122, 189–201 (2018)

    Article  Google Scholar 

  • Avikal, S., Singh, R., Rashmi, R.: QFD and Fuzzy Kano model based approach for classification of aesthetic attributes of SUV car profile. J. Intell. Manuf. 31(2), 271–284 (2020)

    Article  Google Scholar 

  • Ayoola Oke, S.: Manufacturing quality function deployment: literature review and future trends. Eng. J. 17(3), 79–103 (2013)

    Article  Google Scholar 

  • Bevilacqua, M., Ciarapica, F.E., Marchetti, B.: Development and test of a new fuzzy-QFD approach for characterizing customers rating of extra virgin olive oil. Food Qual. Prefer. 24(1), 75–84 (2012)

    Article  Google Scholar 

  • Braglia, M., Fantoni, G., Frosolini, M.: The house of reliability. Int. J. Qualit. Reliab. Manag. 24(4), 420–440 (2007)

    Article  Google Scholar 

  • Buyukozkan, G., Cifci, G.: A new incomplete preference relations based approach to quality function deployment. Inf. Sci. 206, 30–41 (2012)

    Article  Google Scholar 

  • Buyukozkan, G., Çifçi, G.: An integrated QFD framework with multiple formatted and incomplete preferences: a sustainable supply chain application. Appl. Soft Comput. 13(9), 3931–3941 (2013)

    Article  Google Scholar 

  • Buyukozkan, G., Guleryuz, S.: Extending fuzzy QFD methodology with GDM approaches: an application for IT planning in collaborative product development. Int. J. Fuzzy Syst. 17(4), 544–558 (2015)

    Article  Google Scholar 

  • Buyukozkan, G., Feyzioglu, O., Ruan, D.: Fuzzy group decision-making to multiple preference formats in quality function deployment. Comput. Ind. 58(5), 392–402 (2007)

    Article  Google Scholar 

  • Carnevalli, J.A., Miguel, P.C.: Review, analysis and classification of the literature on QFD-types of research, difficulties and benefits. Int. J. Prod. Econ. 114(2), 737–754 (2008)

    Article  Google Scholar 

  • Chan, L.K., Wu, M.L.: Quality function deployment: a comprehensive review of its concepts and methods. Qual. Eng. 15(1), 23–35 (2002a)

    Article  Google Scholar 

  • Chan, L.K., Wu, M.L.: Quality function deployment: a literature review. Eur. J. Oper. Res. 143(3), 463–497 (2002b)

    Article  Google Scholar 

  • Chan, L.K., Wu, M.L.: A systematic approach to quality function deployment with a full illustrative example. Omega 33(2), 119–139 (2005)

    Article  Google Scholar 

  • Chen, C.: CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inform. Sci. Technol. 57(3), 359–377 (2006)

    Article  Google Scholar 

  • Chen, L.H., Weng, M.C.: An evaluation approach to engineering design in QFD processes using fuzzy goal programming models. Eur. J. Oper. Res. 172(1), 230–248 (2006)

    Article  Google Scholar 

  • Chen, C.Y., Chen, L.C., Lin, L.: Methods for processing and prioritizing customer demands in variant product design. IIE Trans. 36(3), 203–219 (2004)

    Article  Google Scholar 

  • Chen, Y.Z., Fung, R.Y.K., Tang, J.F.: Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator. Eur. J. Oper. Res. 174(3), 1553–1566 (2006)

    Article  Google Scholar 

  • Cherif, M.S., Chabchoub, H., Aouni, B.: Integrating customer’s preferences in the QFD planning process using a combined benchmarking and imprecise goal programming model. Int. Trans. Oper. Res. 17(1), 85–102 (2010)

    Article  Google Scholar 

  • Dat, L.Q., Phuong, T.T., Kao, H.P., Chou, S.Y., Nghia, P.V.: A new integrated fuzzy QFD approach for market segments evaluation and selection. Appl. Math. Model. 39(13), 3653–3665 (2015)

    Article  Google Scholar 

  • Dawson, D., Askin, R.G.: Optimal new product design using quality function deployment with empirical value functions. Qual. Reliab. Eng. Int. 15(1), 17–32 (1999)

    Article  Google Scholar 

  • Efe, B.: Fuzzy cognitive map based quality function deployment approach for dishwasher machine selection. Appl. Soft Comput. 83, 105660 (2019)

    Article  Google Scholar 

  • Fahimnia, B., Tang, C.S., Davarzani, H., Sarkis, J.: Quantitative models for managing supply chain risks: a review. Eur. J. Oper. Res. 247(1), 1–15 (2015)

    Article  Google Scholar 

  • Feng, Y., Hong, Z., Tian, G., Li, Z., Tan, J., Hu, H.: Environmentally friendly MCDM of reliability-based product optimisation combining DEMATEL-based ANP, interval uncertainty and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). Inf. Sci. 442–443, 128–144 (2018)

    Article  Google Scholar 

  • Feng, Y., Zhou, M., Tian, G., Li, Z., Zhang, Z., Zhang, Q., Tan, J.: Target disassembly sequencing and scheme evaluation for CNC machine tools using improved multiobjective ant colony algorithm and fuzzy integral. IEEE Trans. Syst. Man Cybern. Syst. 49(12), 2438–2451 (2019)

    Article  Google Scholar 

  • Ferreira, F.A.F., Santos, S.P.: Two decades on the MACBETH approach: a bibliometric analysis. Ann. Oper. Res. 296(1–2), 901–925 (2021)

    Article  Google Scholar 

  • Franceschini, F., Maisano, D.: Prioritization of QFD customer requirements based on the law of comparative judgments. Qual. Eng. 27(4), 437–449 (2015)

    Article  Google Scholar 

  • Fung, R.Y.K., Tang, J., Tu, Y., Wang, D.: Product design resources optimization using a non-linear fuzzy quality function deployment model. Int. J. Prod. Res. 40(3), 585–599 (2002)

    Article  Google Scholar 

  • Ganbat, T., Chong, H.Y., Liao, P.C., Wu, Y.D.: A bibliometric review on risk management and building information modeling for international construction. Adv. Civil Eng. 2018, 8351679 (2018)

    Article  Google Scholar 

  • Garg, H., Chen, S.M.: Multiattribute group decision making based on neutrality aggregation operators of q-rung orthopair fuzzy sets. Inf. Sci. 517, 427–447 (2020)

    Article  Google Scholar 

  • Geum, Y., Kwak, R., Park, Y.: Modularizing services: a modified HoQ approach. Comput. Ind. Eng. 62(2), 579–590 (2012)

    Article  Google Scholar 

  • Guo, Y.M., Huang, Z.L., Guo, J., Guo, X.R., Li, H., Liu, M.Y., Ezzeddine, S., Nkeli, M.J.: A bibliometric analysis and visualization of blockchain. Futur. Gener. Comput. Syst. 116, 316–332 (2021)

    Article  Google Scholar 

  • Haktanır, E., Kahraman, C.: A novel interval-valued pythagorean fuzzy QFD method and its application to solar photovoltaic technology development. Comput. Ind. Eng. 132, 361–372 (2019)

    Article  Google Scholar 

  • Hauser, J.R.: The house of quality. Harv. Bus. Rev. 66, 63–73 (1988)

    Google Scholar 

  • Hou, L.X., Liu, R., Liu, H.C., Jiang, S.: Two decades on human reliability analysis: a bibliometric analysis and literature review. Annal. Nucl. Energy 151, 107969 (2021)

    Article  Google Scholar 

  • 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(5), 1283–1299 (2019)

    Article  Google Scholar 

  • Huang, J., You, J.X., Liu, H.C., Song, M.S.: Failure mode and effect analysis improvement: a systematic literature review and future research agenda. Reliab. Eng. Syst. Saf. 199, 106885 (2020)

    Article  Google Scholar 

  • Jiang, S., Shi, H., Lin, W., Liu, H.C.: A large group linguistic Z-DEMATEL approach for identifying key performance indicators in hospital performance management. Appl. Soft Comput. 86, 105900 (2020)

    Article  Google Scholar 

  • Kahraman, C., Ertay, T., Buyukozkan, G.: A fuzzy optimization model for QFD planning process using analytic network approach. Eur. J. Oper. Res. 171(2), 390–411 (2006)

    Article  Google Scholar 

  • Karsak, E.E.: Fuzzy multiple objective programming framework to prioritize design requirements in quality function deployment. Comput. Ind. Eng. 47(2–3), 149–163 (2004)

    Article  Google Scholar 

  • Karsak, E.E., Dursun, M.: An integrated supplier selection methodology incorporating QFD and DEA with imprecise data. Expert Syst. Appl. 41(16), 6995–7004 (2014)

    Article  Google Scholar 

  • Karsak, E.E., Sozer, S., Alptekin, S.E.: Product planning in quality function deployment using a combined analytic network process and goal programming approach. Comput. Ind. Eng. 44(1), 171–190 (2003)

    Article  Google Scholar 

  • Khaldi, H., Prado-Gascó, V.: Bibliometric maps and co-word analysis of the literature on international cooperation on migration. Qual. Quant. (2021). https://doi.org/10.1007/s11135-020-01085-4

    Article  Google Scholar 

  • Kim, K.J., Moskowitz, H., Dhingra, A., Evans, G.: Fuzzy multicriteria models for quality function deployment. Eur. J. Oper. Res. 121(3), 504–518 (2000)

    Article  Google Scholar 

  • Kutlu Gündoğdu, F., Kahraman, C.: A novel spherical fuzzy QFD method and its application to the linear delta robot technology development. Eng. Appl. Artif. Intell. 87, 103348 (2020)

    Article  Google Scholar 

  • Kutschenreiter-Praszkiewicz, I.: Application of neural network in QFD matrix. J. Intell. Manuf. 24(2), 397–404 (2013)

    Article  Google Scholar 

  • Lazaridis, A., Fachantidis, A., Vlahavas, I.: Deep reinforcement learning: a state-of-the-art walkthrough. J. Artif. Intell. Res. 69, 1421–1471 (2021)

    Article  Google Scholar 

  • Lee, Y.C., Sheu, L.C., Tsou, Y.G.: Quality function deployment implementation based on Fuzzy Kano model: an application in PLM system. Comput. Ind. Eng. 55(1), 48–63 (2008)

    Article  Google Scholar 

  • Lee, A.H.I., Kang, H.Y., Lin, C.Y., Chen, J.S.: A novel fuzzy quality function deployment framework. Qualit. Technol. Quant. Manag. 14(1), 44–73 (2017)

    Article  Google Scholar 

  • Li, Y.L., Tang, J.F., Luo, X.G., Xu, J.: An integrated method of rough set, Kano’s model and AHP for rating customer requirements’ final importance. Expert Syst. Appl. 36(3), 7045–7053 (2009)

    Article  Google Scholar 

  • Li, Y.L., Tang, J.F., Luo, X.G.: An ECI-based methodology for determining the final importance ratings of customer requirements in MP product improvement. Expert Syst. Appl. 37(9), 6240–6250 (2010)

    Article  Google Scholar 

  • Li, Y.L., Chin, K.S., Luo, X.G.: Determining the final priority ratings of customer requirements in product planning by MDBM and BSC. Expert Syst. Appl. 39(1), 1243–1255 (2012a)

    Article  Google Scholar 

  • Li, Y.L., Tang, J.F., Chin, K.S., Luo, X.G., Pu, Y., Jiang, Y.S.: On integrating multiple type preferences into competitive analyses of customer requirements in product planning. Int. J. Prod. Econ. 139(1), 168–179 (2012b)

    Article  Google Scholar 

  • Li, Y.L., Du, Y.F., Chin, K.S.: Determining the importance ratings of customer requirements in quality function deployment based on interval linguistic information. Int. J. Prod. Res. 56(14), 4692–4708 (2018)

    Article  Google Scholar 

  • Liao, H.C., Chang, Y.H., Wu, D., Gou, X.J.: Improved approach to quality function deployment based on pythagorean fuzzy sets and application to assembly robot design evaluation. Front. Eng. Manag. 7(2), 196–203 (2020)

    Article  Google Scholar 

  • Liu, Y.Y., Zhou, J., Chen, Y.Z.: Using fuzzy non-linear regression to identify the degree of compensation among customer requirements in QFD. Neurocomputing 142, 115–124 (2014)

    Article  Google Scholar 

  • Liu, Y.Y., Chen, Y.Z., Zhou, J., Zhong, S.Y.: Fuzzy linear regression models for QFD using optimized h values. Eng. Appl. Artif. Intell. 39, 45–54 (2015)

    Article  Google Scholar 

  • Liu, J., Chen, Y.Z., Zhou, J., Yi, X.J.: An exact expected value-based method to prioritize engineering characteristics in fuzzy quality function deployment. Int. J. Fuzzy Syst. 18(4), 630–646 (2016)

    Article  Google Scholar 

  • Liu, H.C., You, X.Y., Tsung, F., Ji, P.: An improved approach for failure mode and effect analysis involving large group of experts: an application to the healthcare field. Qual. Eng. 30(4), 762–775 (2018a)

    Article  Google Scholar 

  • Liu, Y.Y., Han, Y.L., Zhou, J., Chen, Y.Z., Zhong, S.Y.: Establishing the relationship matrix in QFD based on fuzzy regression models with optimized h values. Soft. Comput. 22(17), 5603–5615 (2018b)

    Article  Google Scholar 

  • Liu, H.C., Wu, S.M., Wang, Z.L., Li, X.Y.: A new method for quality function deployment with extended prospect theory under hesitant linguistic environment. IEEE Trans. Eng. Manag. 68(2), 442–451 (2021)

    Article  Google Scholar 

  • Mehrjerdi, Y.Z.: Quality function deployment and its extensions. Int. J. Qualit. Reliab. Manag. 27(6), 616–640 (2010)

    Article  Google Scholar 

  • Miao, Y.W., Liu, Y.Y., Chen, Y.Z., Zhou, J., Ji, P.: Two uncertain chance-constrained programming models to setting target levels of design attributes in quality function deployment. Inf. Sci. 415, 156–170 (2017)

    Article  Google Scholar 

  • Mistarihi, M.Z., Okour, R.A., Mumani, A.A.: An integration of a QFD model with Fuzzy-ANP approach for determining the importance weights for engineering characteristics of the proposed wheelchair design. Appl. Soft Comput. 90, 106136 (2020)

    Article  Google Scholar 

  • Morente-Molinera, J.A., Wu, X., Morfeq, A., Al-Hmouz, R., Herrera-Viedma, E.: A novel multi-criteria group decision-making method for heterogeneous and dynamic contexts using multi-granular fuzzy linguistic modelling and consensus measures. Inf. Fusion 53, 240–250 (2020)

    Article  Google Scholar 

  • Motlagh, S.M.H., Behzadian, M., Ignatius, J., Goh, M., Sepehri, M.M., Hua, T.K.: Fuzzy promethee GDSS for technical requirements ranking in HOQ. Int. J. Adv. Manuf. Technol. 76(9–12), 1993–2002 (2015)

    Article  Google Scholar 

  • Nahm, Y.E., Ishikawa, H., Inoue, M.: New rating methods to prioritize customer requirements in QFD with incomplete customer preferences. Int. J. Adv. Manuf. Technol. 65(9–12), 1587–1604 (2013)

    Article  Google Scholar 

  • Pal, S.K., Bhoumik, D., Bhunia Chakraborty, D.: Granulated deep learning and Z-numbers in motion detection and object recognition. Neural Comput. Appl. 32(21), 16533–16548 (2020)

    Article  Google Scholar 

  • Ping, Y.J., Liu, R., Lin, W., Liu, H.C.: A new integrated approach for engineering characteristic prioritization in quality function deployment. Adv. Eng. Inf. 45, 101099 (2020)

    Article  Google Scholar 

  • Prasad, B.: Review of QFD and related deployment techniques. J. Manuf. Syst. 17(3), 221–234 (1998)

    Article  Google Scholar 

  • Shahin, A., Bagheri Iraj, E., Vaez Shahrestani, H.: Developing the C-shaped QFD 3D Matrix for service applications with a case study in banking services. Int. J. Qualit. Reliab. Manag. 35(1), 109–125 (2018)

    Article  Google Scholar 

  • Shi, Y.L., Peng, Q.J.: A spectral clustering method to improve importance rating accuracy of customer requirements in QFD. Int. J. Adv. Manuf. Technol. 107(5–6), 2579–2596 (2020)

    Article  Google Scholar 

  • Sivasamy, K., Arumugam, C., Devadasan, S.R., Murugesh, R., Thilak, V.M.M.: Advanced models of quality function deployment: a literature review. Qual. Quant. 50(3), 1399–1414 (2016)

    Article  Google Scholar 

  • Song, W., Ming, X., Han, Y.: Prioritising technical attributes in QFD under vague environment: a rough-grey relational analysis approach. Int. J. Prod. Res. 52(18), 5528–5545 (2014)

    Article  Google Scholar 

  • Tandon, A., Kaur, P., Mäntymäki, M., Dhir, A.: Blockchain applications in management: a bibliometric analysis and literature review. Technol. Forecast. Soc. Chang. 166, 120649 (2021)

    Article  Google Scholar 

  • Tian, G., Zhang, H., Feng, Y., Wang, D., Peng, Y., Jia, H.: Green decoration materials selection under interior environment characteristics: a grey-correlation based hybrid MCDM method. Renew. Sustain. Energy Rev. 81, 682–692 (2018a)

    Article  Google Scholar 

  • Tian, Z.P., Wang, J.Q., Zhang, H.Y.: Hybrid single-valued neutrosophic MCGDM with QFD for market segment evaluation and selection. J. Intell. Fuzzy Syst. 34(1), 177–187 (2018b)

    Article  Google Scholar 

  • Tian, Z.P., Nie, R.X., Wang, J.Q., Li, L.: Group multigranular linguistic QFD for prioritizing service designs with combined weighting method. Expert Syst. (2019). https://doi.org/10.1111/exsy.12419

    Article  Google Scholar 

  • Tian, G., Hao, N., Zhou, M., Pedrycz, W., Zhang, C., Ma, F., Li, Z.: Fuzzy grey Choquet Integral for evaluation of multicriteria decision making problems with interactive and qualitative indices. IEEE Trans. Syst. Man Cybern. Syst. 51(3), 1855–1868 (2021)

    Google Scholar 

  • Wang, S.Y.: Constructing the complete linguistic-based and gap-oriented quality function deployment. Expert Syst. Appl. 37(2), 908–912 (2010)

    Article  Google Scholar 

  • Wang, Y.M.: A fuzzy-normalisation-based group decision-making approach for prioritising engineering design requirements in QFD under uncertainty. Int. J. Prod. Res. 50(23), 6963–6977 (2012)

    Article  Google Scholar 

  • Wang, X.T., Xiong, W.: An integrated linguistic-based group decision-making approach for quality function deployment. Expert Syst. Appl. 38(12), 14428–14438 (2011)

    Article  Google Scholar 

  • Wang, X., Fang, H., Song, W.: Technical attribute prioritisation in QFD based on cloud model and grey relational analysis. Int. J. Prod. Res. 58(19), 5751–5768 (2020)

    Article  Google Scholar 

  • Wang, X., Xu, Z., Su, S.F., Zhou, W.: A comprehensive bibliometric analysis of uncertain group decision making from 1980 to 2019. Inf. Sci. 547, 328–353 (2021)

    Article  Google Scholar 

  • Wasserman, G.S.: On how to prioritize design requirements during the QFD planning process. IIE Trans. 25(3), 59–65 (1993)

    Article  Google Scholar 

  • Wu, H.Y., Lin, H.Y.: A hybrid approach to develop an analytical model for enhancing the service quality of e-learning. Comput. Educ. 58(4), 1318–1338 (2012)

    Article  Google Scholar 

  • Wu, S.M., Liu, H.C., Wang, L.E.: Hesitant fuzzy integrated MCDM approach for quality function deployment: a case study in electric vehicle. Int. J. Prod. Res. 55(15), 4436–4449 (2016)

    Article  Google Scholar 

  • Wu, S.M., You, X.Y., Liu, H.C., Wang, L.E.: Improving quality function deployment analysis with the cloud MULTIMOORA method. Int. Trans. Oper. Res. 27(3), 1600–1621 (2020)

    Article  Google Scholar 

  • Xiao, J., Wang, X., Zhang, H.: Managing personalized individual semantics and consensus in linguistic distribution large-scale group decision making. Inf. Fusion 53, 20–34 (2020)

    Article  Google Scholar 

  • Xu, J., Xu, X., Xie, S.Q.: A comprehensive review on recent developments in quality function deployment. Int. J. Prod. Qualit. Manag. 6(4), 457–494 (2010)

    Google Scholar 

  • Xu, X.H., Du, Z.J., Chen, X.H., Cai, C.G.: Confidence consensus-based model for large-scale group decision making: A novel approach to managing non-cooperative behaviors. Inf. Sci. 477, 410–427 (2019)

    Article  Google Scholar 

  • Xu, S., Zhang, X., Feng, L., Yang, W.: Disruption risks in supply chain management: a literature review based on bibliometric analysis. Int. J. Prod. Res. 58(11), 3508–3526 (2020a)

    Article  Google Scholar 

  • Xu, X., Zhang, Q., Chen, X.: Consensus-based non-cooperative behaviors management in large-group emergency decision-making considering experts’ trust relations and preference risks. Knowl. Based Syst. 190, 105108 (2020b)

    Article  Google Scholar 

  • Yager, R.R.: Pythagorean membership grades in multicriteria decision making. IEEE Trans. Fuzzy Syst. 22(4), 958–965 (2014)

    Article  Google Scholar 

  • Yan, H.B., Ma, T.: A group decision-making approach to uncertain quality function deployment based on fuzzy preference relation and fuzzy majority. Eur. J. Oper. Res. 241(3), 815–829 (2015)

    Article  Google Scholar 

  • Yang, Q., Li, Y.L., Chin, K.S.: An ordinal scale-based GDM approach to prioritize customer requirements in QFD product planning. J. Intell. Fuzzy Syst. 37(3), 4349–4367 (2019)

    Article  Google Scholar 

  • Ye, J., Zhan, J., Xu, Z.: A novel decision-making approach based on three-way decisions in fuzzy information systems. Inf. Sci. 541, 362–390 (2020)

    Article  Google Scholar 

  • Zare Mehrjerdi, Y.: Quality function deployment and its extensions. Int. J. Qualit. Reliab. Manag. 27(6), 616–640 (2010)

    Article  Google Scholar 

  • Zhai, L.Y., Khoo, L.P., Zhong, Z.W.: A rough set enhanced fuzzy approach to quality function deployment. Int. J. Adv. Manuf. Technol. 37(5–6), 613–624 (2008)

    Article  Google Scholar 

  • Zhong, S.Y., Zhou, J., Chen, Y.Z.: Determination of target values of engineering characteristics in QFD using a fuzzy chance-constrained modelling approach. Neurocomputing 142, 125–135 (2014)

    Article  Google Scholar 

  • Zhu, L., Liu, X.F.: Technical target setting in QFD for web service systems using an artificial neural network. IEEE Trans. Serv. Comput. 3(4), 338–352 (2010)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 72001196), the Zhejiang Provinvcial Natural Science Foundation of China (Grant No. LQ21G010004) and the Fundamental Research Funds for the Central Universities.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hu-Chen Liu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, J., Mao, LX., Liu, HC. et al. Quality function deployment improvement: A bibliometric analysis and literature review. Qual Quant 56, 1347–1366 (2022). https://doi.org/10.1007/s11135-021-01179-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11135-021-01179-7

Keywords

Navigation