Product design and selection using fuzzy QFD and fuzzy MCDM approaches

Liu, Hao-Tien

doi:10.1016/j.apm.2010.07.014

Cited by 107 publications

(47 citation statements)

References 30 publications

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“…The applications of MCDM are numerous and it has been applied to human resource management (Shih et al, 2007), transportation (Tsaur et al, 2002), portfolio optimization (Ehrgott et al, 2004), product design (Liu, 2011), vendor selection (Shyur and Shih, 2006) and visual inspection (Verma et al, 2015). The most commonly used method for MCDM is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).…”

Section: Introductionmentioning

confidence: 99%

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

Verma

Rajasankar

2017

Applied Soft Computing

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In multi-criteria decision making (MCDM) problems, ratings are assigned to the alternatives on different criteria by the expert group. In this paper, we propose a thermodynamically consistent model for MCDM using the analogies for thermodynamical indicators -energy, exergy and entropy. The most commonly used method for analysing MCDM problem is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The conventional TOPSIS method uses a measure similar to that of energy for the ranking of alternatives. We demonstrate that the ranking of the alternatives is more meaningful if we use exergy in place of energy. The use of exergy is superior due to the inclusion of a factor accounting for the quality of the ratings by the expert group. The unevenness in the ratings by the experts is measured by entropy. The procedure for the calculation of the thermodynamical indicators is explained in both crisp and fuzzy environment. Finally, two case studies are carried out to demonstrate effectiveness of the proposed model.

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Section: Introductionmentioning

confidence: 99%

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

Verma

Rajasankar

2017

Applied Soft Computing

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“…According to Zhaiet al (2009), the methods and approaches can be classified into two categories, namely the numerical methods and the non-numerical methods. The non-numerical approach, basically involves the traditional design evaluation approach which includes methods like; concept screening (Ulrich, & Eppinger, 2000) and concept selection and evaluation (Pugh, 1996), while the numerical methods comprises of methods like decision matrixes (King & Sivaloganathan, 1999), quality function deployment (Mariniet al , 2016), fuzzy set (FS) concepts (Aikhuele & Turan, 2017;Akay et al, 2011;Jenab et al, 2013;Liu 2011), grey relation analysis (Zhai et al, 2009). …”

Section: Introductionmentioning

confidence: 99%

Interval-valued intuitionistic fuzzy multi-criteria model for design concept selection

Aikhuele¹

2017

10.5267/j.msl

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This paper presents a new approach for design concept selection by using an integrated Fuzzy Analytical Hierarchy Process (FAHP) and an Interval-valued intuitionistic fuzzy modified TOP-SIS (IVIF-modified TOPSIS) model. The integrated model which uses the improved score function and a weighted normalized Euclidean distance method for the calculation of the separation measures of alternatives from the positive and negative intuitionistic ideal solutions provides a new approach for the computation of intuitionistic fuzzy ideal solutions. The results of the two approaches are integrated using a reflection defuzzification integration formula. To ensure the feasibility and the rationality of the integrated model, the method is successfully applied for evaluating and selecting some design related problems including a real-life case study for the selection of the best concept design for a new printed-circuit-board (PCB) and for a hypothetical example. The model which provides a novel alternative, has been compared with similar computational methods in the literature.

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“…Companies have to develop new products that meet customer requirements in a shorter time to improve their competitive advantage. Companies realize the importance of effectively translating customer requirements into engineering characteristics and quality factors that should be considered in product design and development H.-T. Liu [2], C.C. Otel [3], I.A.…”

Section: Introductionmentioning

confidence: 99%

“…Mostly, the result of market survey and linguistic variables used are imprecise or uncertain, usually resulting in biased analysis results. In order to cope with this problem, a number of scholars have applied the fuzzy set theory to QFD and developed various fuzzy QFD approaches H.-T. Liu [2]. The approaches contain conventional QFD computation using fuzzy variables E. Bottani, A. Rizzi [7], fuzzy tendency analysis X.X.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy quality function deployment approach to improve a component of a supervisory control and data acquisition system

2017

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Abstract-Monitoring and control of electric transformer stations, frequently spread out over small or large geographical areas, are achieved with supervisory control and data acquisition (SCADA). Quality function deployment (QFD) is a valuable analyzing tool in product design and development. To solve the uncertainty or inherent imprecision in QFD, many researchers have applied the fuzzy set theory to QFD and have developed various fuzzy QFD approaches. The literature regarding applying fuzzy QFD for analyzing subsystems of SCADA, to the best of our knowledge, remains inexistent. In this paper, a fuzzy QFD approach is used to effectively determine the design requirements of a SCADA component.

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Product design and selection using fuzzy QFD and fuzzy MCDM approaches

Cited by 107 publications

References 30 publications

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

A thermodynamical approach towards group multi-criteria decision making (GMCDM) and its application to human resource selection

Interval-valued intuitionistic fuzzy multi-criteria model for design concept selection

A fuzzy quality function deployment approach to improve a component of a supervisory control and data acquisition system

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