A hybrid fuzzy quality function deployment framework using cognitive network process and aggregative grading clustering: An application to cloud software product development

Kevin Kam Fung Yuen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

Quality function deployment (QFD) is an essential decision tool for product development in various domains. QFD enables the cross-functional team to translate the customer requirements into engineering characteristics during product development. Whilst there are some limitations for criteria evaluation and analysis in QFD, this study proposes a hybrid framework of Fuzzy Cognitive Network Process, Aggregative Grading Clustering, and Quality Function Deployment (F-CNP-AGC-QFD) for the criteria evaluation and analysis in QFD. The fuzzy number applied to the QFD, i.e. FQFD, enables rating flexibility for the expert judgment to handle uncertainty. The Fuzzy Cognitive Network Process (FCNP) is used for the criteria weights/priorities evaluation. The Fuzzy Aggregative Grading Clustering (FAGC) classifies the weights/priorities as ordinal grades. The proposed hybrid QFD approach applied to the cloud software product development is demonstrated to show the validity and applicability.

Original languageEnglish
Pages (from-to)95-106
Number of pages12
JournalNeurocomputing
Volume142
DOIs
Publication statusPublished - 22 Oct 2014

Keywords

  • Fuzzy clustering
  • Fuzzy decision making
  • New product development
  • Quality function deployment
  • Software development

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