A new hesitant fuzzy QFD approach: An application to computer workstation selection
Graphical abstract
Introduction
A workstation is a customized computer that is designed for specific scientific or technical application. Increasing competition and technological innovation in the industry and business world in general brings about new developments in the workstation design. However, workstations are usually designed arbitrarily with little consideration to the specific needs and requirements of their users. Considering additional benefits of tailor-made workstations that are customized for specific uses and needs, a customer-driven approach in workstation design would benefit companies. Such an approach would not only capture customers’ perspectives, but also raise the overall level of their satisfaction level. Quality function deployment (QFD) is a customer-driven tool that is widely used for product planning purposes. It can be beneficial to reach higher levels in customer satisfaction [1], [2]. Good design requires consideration of design aspects that clients want and expect. To address this, QFD uses a matrix called House of Quality (HOQ) [3] that translates Customer Needs or Requirements (CRs) into engineering characteristics or Design Requirements (DRs). The HOQ is constructed with the importance weights of each of the CRs, as well as the correlation matrix among DRs and the relationship matrix between CRs and DRs [1], [2], [3], [4], [5].
The importance levels of CRs, functional relationships among CRs and DRs, and the assessments of alternatives based on DRs are difficult to express precisely. Although crisp data are needed to design workstations, experts usually prefer to provide their evaluations in linguistic terms. The fuzzy set theory lets these linguistic assessments be incorporated into numerical analyses. The ordinary fuzzy sets have been recently extended to Type 2 fuzzy sets, hesitant fuzzy sets, intuitionistic fuzzy sets, non-stationary fuzzy sets and fuzzy multisets [6]. Hesitant fuzzy sets (HFS), which are developed by Torra [7], allow more than one value for defining the membership value of an element, enabling an expert better express his/her assessment [8]. In this paper, we prefer to use hesitant linguistic term sets (HFLTS) in the development of a new fuzzy QFD approach since HFLTS enable the integration of various linguistic evaluations assigned by experts as an inclusive linguistic interval. HFLTS have been used in several papers in the literature [9], [10], [11], [12], [13], [14], [15], [16].
Main features of the proposed hesitant fuzzy QFD approach are the use of HFLTS in the pairwise comparisons among CRs; the use of relations between CRs and DRs; the use of correlations among DRs, and the evaluation of alternatives. The weights of the CRs are determined by a hierarchical and pairwise comparison-based approach while the alternatives are ranked by using a hesitant fuzzy TOPSIS method. Besides, we propose a new approach taking the hesitant correlations among DRs into account in the HOQ operations. To the best of our knowledge, there is no QFD study based on hesitant fuzzy sets in the literature and this study is different from the other existing approaches since it considers the experts’ hesitancies in each phase of the QFD approach.
The remainder of this paper is structured as the following; Section 2 presents basic concepts of QFD and a literature review of fuzzy QFD methodology. In Section 3, the main concepts of HFS and HFTLS are given. Section 4 gives the proposed decision making approach which is based on hesitant fuzzy QFD. In Section 5, a case study is provided to demonstrate the applicability of the proposed method. The last section concludes the paper and gives some perspectives.
Section snippets
Literature survey on fuzzy QFD
The overall methodological structure is based on the QFD technique, supported by a hesitant fuzzy set approach, where linguistic data are considered. In the following, first, basic QFD terminology on classical QFD is given. Then a literature review on fuzzy set extensions in QFD is given.
Hesitant fuzzy linguistic term sets (HFLTS)
Hesitant fuzzy sets (HFSs) are the extensions of fuzzy sets which can solve the difficulties in determining the membership degree of an element [7]. It represents the hesitancy where there are possible values for membership and it is not clear which one is the right value. Definition 1 A hesitant fuzzy set (HFS) on X, where X is a fixed set, can be defined as follows:
Hesitant fuzzy sets can be
Hesitant fuzzy QFD: steps of the methodology
Hesitant Fuzzy Sets has the advantage of considering the hesitancy of experts under uncertainty. Neither classical QFD method nor ordinary fuzzy QFD method can handle this hesitancy.
In this section, we will first give the steps of the proposed hesitant fuzzy QFD methodology and then extend the same steps for the design problems having correlations among DRs.
Case study
In this section, three computer workstations are compared by using the proposed hesitant QFD method based on the determined CRs and DRs. First we give the problem definition and implement the proposed method to the computer workstation selection problem. Later, a sensitivity analysis and comparisons with classical and ordinary fuzzy QFD approaches are presented.
Conclusion
Hesitancy is an inherent part of decision making process. Experts generally have difficulty to establish the degree of membership of fuzzy set because of the time pressure, lack of knowledge or data, etc. To overcome these difficulties, the concept of hesitant fuzzy set which permitted the membership degree having a set of possible values can be employed. We have proposed hesitant fuzzy QFD since it can reflect the human’s hesitancy more objectively than the other classical extensions of fuzzy
References (51)
Reviewof QFD and related deployment techniques
J. Manuf. Syst.
(1998)- et al.
Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets
Knowl. Based Syst.
(2015) - et al.
Approaches to manage hesitant fuzzy linguistic information based on the cosine distance and similarity measures for HFLTSs and their application in qualitative decision making
Expert Syst. Appl.
(2015) - et al.
An outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets
Inf. Sci.
(2014) - et al.
Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model
Expert Syst. Appl.
(2015) - et al.
Enhancing enterprise agility by deploying agile drivers, capabilities and providers
Inf. Sci.
(2011) - et al.
Quality function deployment: a literature review
Eur. J. Oper. Res.
(2002) - et al.
Review, analysis and classification of the literature on QFD-Types of research, difficulties and benefits
Int. J. Prod. Econ.
(2008) - et al.
A new incomplete preference relations based approach to quality function deployment
Inf. Sci.
(2012) - et al.
An integrated QFD framework with multiple formatted and incomplete preferences: a sustainable supply chain application
Appl. Soft Comput.
(2013)
Fuzzy group decision making to multiple preference formats in quality function deployment
Comput. Ind.
A fuzzy optimization model for QFD planning process using analytic network approach
Eur. J. Oper. Res.
An integrated fuzzy QFD model proposal on routing of shipping investment decisions in crude oil tanker market
Expert Syst. Appl.
A rough set approach for estimating correlation measures in quality function deployment
Inf. Sci.
Rough set-based approach for modeling relationship measures in product planning
Inf. Sci.
A methodology of determining aggregated importance of engineering characteristics in QFD
Comput. Ind. Eng.
The extension of quality function deployment based on 2-tuple linguistic representation model for product design under multigranularity linguistic environment
Math. Probl. Eng
Exploiting 2-tuple linguistic representational model for constructing HOQ-based failure modes and effects analysis
Comput. Ind. Eng.
An integrated fuzzy MCDM approach for supplier evaluation and selection
Comput. Ind. Eng.
An entropy measure definition for finite interval-valued hesitant fuzzy sets
Knowl. Based Syst.
Generalized hesitant fuzzy sets and their application in decision support system
Knowl. Based Syst.
Multicriteria linguistic decision making based on hesitant fuzzy linguistic term sets and the aggregation of fuzzy sets
Inf. Sci.
Fuzzy decision making based on likelihood-based comparison relations of hesitant fuzzy linguistic term sets and hesitant fuzzy linguistic operators
Inf. Sci.
Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: an outranking approach
Knowl. Based Syst.
A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision making
Inf. Sci.
Cited by (142)
Fermatean fuzzy based Quality Function Deployment methodology for designing sustainable mobility hub center
2023, Applied Soft ComputingA decision support model for estimating participation-oriented designs of crowdsourcing platforms based on quality function deployment
2022, Expert Systems with ApplicationsThe interval grey QFD method for new product development: Integrate with LDA topic model to analyze online reviews
2022, Engineering Applications of Artificial IntelligenceCitation Excerpt :Akao (1994) defined QFD as a design and development method aimed at satisfying customers, which translates CRs into design goals and product quality and runs through the whole production stage. It is a market-user-oriented approach to ensure product quality during product development (Onar and Oztaysi, 2016). Generally, there are four successive matrices in the QFD analysis process, and the focus of this study is the first phase product design matrix (Bottani and Rizzi, 2006).