The quality function deployment method under uncertain environment using evidential reasoning: a case study of compressor manufacturing

Shiva Mehrabi-Kandsar (), Abolfazl Mirzazadeh and Aref Gholami-Qadikolaei
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Shiva Mehrabi-Kandsar: Amirkabir University of Technology
Abolfazl Mirzazadeh: Kharazmi University
Aref Gholami-Qadikolaei: Kharazmi University

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 102, 1867-1884

Abstract: Abstract In recent years, the issue of customer satisfaction achieving on the basis of improving service quality has been widely investigated. To achieve this goal, one of well-structured method is quality function deployment (QFD). QFD is an approach defining customer requirements (CRs) and translating them into relevant design requirements (DRs). The successful implementation of QFD requires a significant number of subjective evaluations of both customers and QFD team members. The QFD team members evaluate relationships between DRs and CRs and interrelationships between DRs. The customers evaluate relative importance of each CRs. In the basic QFD, crisp values are used for determining relationships between DRs and CRs, but the mentioned method are not suitable to address the subject of uncertainty, since in most cases QFD team express their opinions with uncertainty and therefore resulting in inappropriate implementation of QFD. This paper aims to apply a QFD method based on evidential reasoning approach to handle uncertain evaluation information provided by QFD team in compressor manufacturing. This method is able to consider uncertainties such as interval, imprecise and incomplete data in utilizing belief structure and then aggregating them to prioritize engineering DRs according to CRs.

Keywords: Quality function deployment; Group decision making; Uncertainty modeling; Evidential reasoning; Preference programming (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s13198-016-0478-3

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