Fuzzy Cluster Analysis on Customer Requirement Elicitation Pattern of QFD

Hong, Y H; Kong, Feng

doi:10.2991/978-94-6239-148-2_75

Cited by 2 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, to analyze customer requirements, researchers have come up with different methods. Such as, Kwong and Bai [ 41 ] proposed the combination method of AHP and QFD to calculate the weight of customer requirements and finally convert it into product attributes to meet customer requirements; Wang and Tseng [ 42 ] used the Bayesian method to transform customer requirements into products variant; Wang et al [ 39 ] developed the gray rough model to analyze customer requirements; Chandha et al [ 43 ] combined Kano model with QFD to sort out customer demand; Nahm [ 44 ] proposed PIR method and CPR method based on QFD for considering customer requirements; Hong and Feng [ 45 ] used the fuzzy dynamic clustering method to analyze and classify the customer requirements based on QFD, etc. These methods all have their own merits, therefore which one of them can be selected according to the actual application.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Clustering analysis [ 45 , 49 ] is a method to cluster indicators by establishing similarity relationship based on the characteristics, degree of intimacy and similarity. Generally speaking, clustering algorithm can be divided into hierarchical clustering, partition clustering and density clustering.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To research the similarity of customer requirements between

and

, the method of correlation coefficient is used as follows [ 45 ]:

where,

…”

Section: Evaluating the Sustainable Operation Of Rail Transit Systmentioning

confidence: 99%

“…The reason seems to be obvious that the fuzzy matrix T has reflexivity and symmetry but not necessarily has transitivity, the fuzzy equivalent matrix should be calculated by taking the Quadratic method [ 45 ]. we start from fuzzy similar matrix

, as follows,

…”

Section: Evaluating the Sustainable Operation Of Rail Transit Systmentioning

confidence: 99%

See 3 more Smart Citations

Research on Evaluating the Sustainable Operation of Rail Transit System Based on QFD and Fuzzy Clustering

Yan

Wang

2020

Entropy

View full text Add to dashboard Cite

The purpose of this study is to evaluate the sustainable operation of rail transit system. In rail transit system, as the most important aspect of negative entropy flow, the effective strategy can offset the increasing entropy of the system and make it have the characteristics of dissipative structure, so as to realize the sustainable operation. At first, this study constructs the Pressure-State-Response(PSR) model to evaluate the sustainable operation of rail transit system. In this PSR model, “pressure” is viewed as customer requirements, which answers the reasons for such changes in rail transit system; “state” refers to the state and environment of system activities, which can be described as the challenges of coping with system pressure; “response” describes the system’s actions to address the challenges posed by customer needs, namely operational strategies. Moreover, then, 13 pressure indices, five state indices and 11 response indices are summarized. In addition, based on quality function deployment (QFD), with 13 pressure indices as input variables, five state indices as customer requirements (CRs) of QFD and 11 response indices as technical attributes (TAs) of QFD, this study proposed the three-phase evaluation method of the sustainable operation of rail transit system to obtain the operational strategy (that is, negative entropy flow): The first phase is to verify that 13 pressure indices can be clustered into five state indices by fuzzy clustering analysis; The second phase is to get the weights of five state indices by evidential reasoning; The third phase is to rate the importance of 11 response indices by integrating fuzzy weighted average and expected value operator. Finally, the proposed model and method of evaluation are applied to the empirical analysis of Shanghai rail transit system. Finally, we come to the conclusion that Shanghai rail transit system should take priority from the following five aspects: “advancement of design standards”, “reliability of subway facilities”, “completeness of operational rules”, “standardization of management operation” and “rationality of passenger flow control”.

show abstract