Bibliometric analysis of quality function deployment with fuzzy systems
Bibliometric analysis of quality function deployment with fuzzy systems
Índice
Research on quality function deployment (QFD) with fuzzy systems has increased since the 2000s. The growing number of QFD applications with fuzzy systems indicates worldwide attention on this field of research. Then, two research questions arise: Are there some trends? And, are there some research gaps? This paper presents bibliometric analysis to answer those questions, performed on data from Scopus database, in a total output of 598 documents. Only articles and reviews were searched. China is the leading country in publication and international collaboration (207 published documents, more than a third of total). The main finding of analysis is the trend of QFD integration with fuzzy and multi-criteria decision-making (MCDM) methods. This could be observed with different applications as new product development, quality management, service quality, and supply chain management, to name a few.
See paper
Akao, Y. (2004), “QFD: Quality function deployment. N”. York: Productivity.
Armacost R. L, Componation P. J, Mullens M. A and Swart. W. W. (1994) “An ahp framework for prioritizing custom requirement in qfd: An industrialized housing application.” IIE Trans., Vol. 26 , pp. 72–79.
Atanassov K. T. (1986). “Intuitionistic fuzzy sets”. Fuzzy Sets and Systems. Vol. 20, pp. 87–96.
Bevilacqua M, Ciarapica F. E. and Giacchetta G. (2006) “A fuzzy–qfd approach to supplier selection”. Supply Manag., Vol. 12 , pp. 14–27.
Bottani E and Rizzi A (2006). “Strategic management of logistics ser-vice: A fuzzy qfd approach” Int. J. Prod. Econ., Vol. 103 , pp. 585–599.
Bouchereau V and Rowlands H (2000). “Methods and techniques to help quality function deployment (qfd)”. Benchmarking. Vol. 7 , pp. 8–20.
Buyukozkan G, Ertay T, Kahraman C and Ruan D (2004). “Determining the importance weights for the design requirements in the house of quality using the fuzzy analytic network approach”. Int. J. Intell. Syst, Vol. 19 , pp. 443–461.
Carnevalli J. A and Miguel P. C. (2008) “Review, analysis and classification of the literature on qfd– types of research, difficulties and benefits”. Int. J. Prod. Econ, Vol. 114 , pp. 737–754.
Chan L. K., Kao H. P. Ng, A and Wu, M. L (1999). “Rating the importance of customer needs in quality function deployment by fuzzy and entropy methods”. Int. J. Prod. Res., Vol. 37 , pp. 2499– 2518.
Chan L.-K and Wu M.-L (2002). “Quality function deployment: A literature review”. Eur. J. Oper. Res, Vol. 143 , pp. 463–497.
Chan L.-K. and Wu M.-L (2005), “A systematic approach to quality function deployment with a full illustrative example”. Omega–Int. J. Manage. S. Vol. 33 , pp. 119–139.
Chen C.-J, Yang S.-M. and Chang S.-C (2014). “A fuzzy integrating model ahp with qfd for assessing technical factors in aviation safety”. Int. J. Mach. Learn. Cyb.. Vol. 5 , pp. 761–774.
Chen L.-H and Weng M.-C (2006). “An evaluation approach to engi-neering design in qfd processes using fuzzy goal programming models”, Eur. J. Oper. Res, Vol. 172 , pp. 230–248.
Chen Y., Fung R. Y. and Tang J (2006). “Rating technical attributes in fuzzy qfd by integrating fuzzy weighted average method and fuzzy expected value operator”. Eur. J. Oper. Res., Vol. 174 , pp. 1553– 1566.
Chen Y., J. Tang, R. Y. K. Fung & Z. Ren. Fuzzy regression-based mathematical programming model for quality function deployment. Int. J. Prod. Res. (2004). Vol. 42, pp. 1009-1027
Chuang P. T.. (2001). “Combining the analytic hierarchy process and quality function deployment for a location decision from a requirement perspective”. Int. J. Adv. Manuf. Tech., Vol. 18 , pp. 842– 849.
Clarivate Analytics (2018). Journal citation reports. URL: https://clarivate.com/products/journal- citation-reports/ access: Nov. 2018.
Egghe L. (2006). “An improvement of the h-index: the g-index”. ISSI Newsletter. (2006). Vol. 2, pp. 8–9.
Falagas M. E., Pitsouni E. I., Malietzis G. A. and Pappas (G) (2008), “Comparison of pubmed, scopus, web of science, and google scholar: strengths and weaknesses”. FASEB J. Vol. 22 , pp. 338–342.
Fung R. Y. K, Popplewell K. and Xie J (1998). “An intelligent hybrid system for customer requirements analysis and product at-tribute targets determination”. Int. J. Prod. Res.., Vol. 36, pp. 13–34.
Garibaldi J. M. and Ozen T. (2007) “Uncertain fuzzy reasoning: A case study in modelling expert decision making”. IEEE T. Fuzzy Syst., Vol. 15 , pp. 16–30.
Govers, C. P. M.(2001). “Qfd not just a tool but a way of quality management”. Int. J. Prod. Econ. (2001). Vol. 69 , pp. 151–159.
Grattan-Guiness I.(1976), “Fuzzy membership mapped onto intervals and many–valued quantities”. Zeitschr. f. math. Logik und Grundlagen d. Math., Vol. 22 , pp. 149–160.
Jian S, Xiu-Yan P., Ying X., Pei-Lei W. and Na-Ji M (2016). “A new method combining qfd with intuitionistic fuzzy sets for web services selection”. Int. J. Multim. and Ubiquit. Eng., Vol. 11 , pp. 107–118.
Kahraman C., Ertay T. and Buyukozkan G (2006) “A fuzzy optimiza-tion model for qfd planning process using analytic network approach”. Eur. J. Oper. Res., Vol. 171 , pp. 390–411
Kahraman C., Öztayşi B. and Onar S. Ç. (2016). “A comprehensive literature review of 50 years of fuzzy set theory”. Int. J. Comput. Intell. Syst., Vol. 9 , pp. 3–24.
Kahraman C., Oztaysi B., Onar S. C. & Dogan O. (2018) “Intuition-istic fuzzy originated interval type-2 fuzzy ahp: an applica-tion to damless hydroelectric power plants”. International Journal of the Analytic Hierarchy Process. Vol. 10 , pp. 266–292.
Karsak E.E..(2004). “Fuzzy multiple objective programming framework to prioritize design requirements in quality function deployment”. Comput. Ind. Eng., Vol. 47 , pp. 149–163.
Khoo L. P. and Hot N. C. (1996). “Framework of a fuzzy quality function deployment system. Int. J. Prod. Res. Vol. 34 , pp. 299–311.
Kim K.-J., Moskowitz H., Dhingra A and Evans G (2000). “Fuzzy multicriteria models for quality function deployment”. Eur. J. Oper. Res., Vol. 121 , pp. 504–518.
Kraslawski A, Koiranen T and Nystrom L (1993). “Concurrent engineering: Robust design in fuzzy environment”. Comput. Chem. Eng. Vol. 17 , S447–S452.
Kulkarni A. V, Aziz B, Shams I and Busse J. W. (2009). “Comparisons of citations in web of science, scopus and google scholar for articles published in general medical journals”. JAMA–J. Am. Med. Assoc., Vol. 302 , pp. 1092–1096.
Kwong C. K. and Bai H (2002).”A fuzzy ahp approach to the de-termination of importance weights of customer requirements in quality function deployment”. J. Intell. Manuf. Vol. 13 , pp. 367–377.
Kwong C. K. and Bai H (2003). “Determining the importance weights for the customer requirements in qfd using a fuzzy ahp with an extent analysis approach”. IIE Trans. Vol. 35, pp. 619–626.
Li M., Jin L. and Wang J (2014). “A new mcdm method combining qfd with topsis for knowledge management system selection from the users perspective in intuitionistic fuzzy environment”. Appl. Soft Comput. Vol. 21, 28–37.
Melin P., Astudillo L., Castillo O., Valdez F. and Garcia M (2013) “Optimal design of type-2 and type-1 fuzzy tracking controllers for autonomous mobile robots under perturbed torques using a new chemical optimization paradigm”. Expert Syst. Appl. Vol. 40, pp. 3185–3195.
Moskowitz H and Kim K (1983). “On assessing the h value in fuzzy linear regression”. Fuzzy Sets Syst. Vol. 58 , pp. 303–327.
Onar S. C., Buyukozkan G., Oztaysi B. and Kahraman C (2016). “A new hesitant fuzzy qfd approach: An application to computer workstation selection”. Appl. Soft Comput, Vol. 46 , pp. 1–16.
Osiro L., Lima Junior F. R. and Carpinetti L. C. R. (2018) “A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics”. Journal of cleaner production. Vol. 183, pp. 964-978
Rodriguez R. M., Martinez L. and Herrera F. (2012), “Hesitant fuzzy linguistic term sets for decision making”, IEEE Transactions on Fuzzy Systems. Vol. 20(1). pp. 109 – 119.
Rodriguez R. M, Bedregal B., Bustince H., Dong Y. C., Farhadinia B., Kahraman C., Martnez L., Torra V., Xu Y. J., Xu Z. S. and Herrera F (2016) “A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. to-wards high quality progress”. Inf. Fusion. Vol. 29, pp. 1566–2535.
Sivasamy K., Arumugam C, Devadasan S. R., Murugesh R. & Thilak V. M. M (2016) “Advanced models of quality function deployment: A literature review”. Quality & Quantity., Vol. 50, pp. 1399– 1414.
Tan J, Fu H.-Z & Ho Y.-S (2014), “A bibliometric analysis of research on proteomics in science citation index expanded”. Scien-tometrics. Vol. 98 , pp. 1473– 1490.
Tang J., Fung R. Y., Xu B. and Wang D. (2002) “A new approach to quality function deployment planning with financial consideration”. Comput. Oper. Res., Vol. 29 , pp. 1447–1463.
Temponi C., Yen J and Tiao W. A (1999) “House of quality: A fuzzy logic-based requirements analysis”. Eur. J. Oper. Res, Vol. 117 , pp. 340–354.
Tong R. M. and Bonissone P. P. (1980). “A linguistic approach to decision making with fuzzy sets”. IEEE Transactions On Systems, Man and Cybernetics., Vol. 10 , pp. 716–723.
Torra V (2010).” Hesitant fuzzy sets”. Int. J. Intell. Syst.. Vol. 25 , pp. 529–539.
Van Eck N. J. and Waltman L (2010). “Software survey: VOSviewer, a computer program for bibliometric mapping”. Scientometrics. Vol. 84 , pp. 523–538.
Vanegas L.V. and Labib A. W (2001) “A fuzzy quality function deployment (fqfd) model for deriving optimum targets”. Int. J. Prod. Res., Vol. 39 , pp. 99–120.
Wang J (1999) “Fuzzy outranking approach to prioritize design requirements in quality function deployment”. Int. J. Prod. Res., Vol. 37 , pp. 899–916.
Wang L., Zhao L., Mao G., Zuo J. & Du H. (2017). “Way to accomplish low carbon development transformation: A bibliometric analysis during 1995- 2014”. Renew Sust. Energ. Rev. Vol. 68 , pp. 57–69.
Wu S. M., Liu H.-C and Wang L.-E (2017), “Hesitant fuzzy integrated mcdm approach for quality function deployment:a case study in electric vehicle”. Int. J. Prod. Res, Vol. 55 , pp. 4436–4449.
Wu S. M., You X. Y., Liu H. C and Wang L. E. (2017). “Improving quality function deployment analysis with the cloud multi-moora method”. Int. Trans. Oper. Vol. 125, pp. 111–123.
Yager R. R. (1986). On the theory of bags. Int. J. Gen. Syst., Vol. 13 , pp. 23–37.
Wang L. Yu, L. and Bao Y (2018). “Technical attributes ratings in fuzzy QFD by integrating interval- valued intuitionistic fuzzy sets and Choquet integral”. Soft Comput Vol. 22 pp. 2015–2024
Yataganbaba A and Kurtbas I (2016). “A scientific approach with bibliometric analysis related to brick and tile drying: A review”. Renew. Sust. Energ. Rev. Vol. 59 , pp. 206–224.
Zadeh L. A.. Fuzzy sets. Inform. Control. (1965). Vol. 8 , pp. 338–353.
Zadeh L. A.. The concept of a linguistic variable and its appli-cations to approximate reasoning–i. Inform. Sci.. (1975). Vol. 8 , pp. 199–249.
Zyoud S. H. and Fuchs-Hanusch D (2017). “A bibliometric-based survey on ahp and topsis techniques”. Expert Syst. Appl. Vol. 78 , pp. 158–181.
Bibliometrics, fuzzy systems, quality function deployment, Scopus