Fuzzy Quality Function Deployment Research Articles

Interval-valued spherical fuzzy quality function deployment methodology: Metaverse collaborative system design application

The metaverse collaborative system (MCS) aims to assist users in working together, sharing resources, and participating in joint activities in the metaverse environment. As an interactive system, identifying essential design requirements (DRs) based on user requirements (URs) during the conceptual design phase of MCS is challenging as it directly affects the cost of subsequent optimization design and user experimentation, as well as user experience. Therefore, we propose a quality function deployment (QFD) method based on multi-criteria decision-making (MCDM) in an interval-valued spherical fuzzy (IVSF) environment to establish a mapping relationship between URs and DRs and identify human-centered DRs to guide the conceptual design process of MCS. Firstly, we summarized the URs for MCS design and calculated their weights using IVSF based analytical hierarchy process (IVSF-AHP). Afterward, we determined DRs based on URs and established the UR-DR relationship in the house of quality of QFD. Next, we integrate the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in the IVSF environment into QFD to determine the priority of DRs. The results indicate that system functional design, scene layout design, compatibility design, and multi-user collaborative optimization design are important DRs for designing MCS and should be carefully considered. We validated the applicability of this method through an urban planning MCS design example and provided a conceptual design case including functional blueprints. Sensitivity analysis and comparative analysis demonstrate the flexibility and reliability of the proposed method.

Global semiconductor supply chain resilience challenges and mitigation strategies: A novel integrated decomposed fuzzy set Delphi, WINGS and QFD model

The recent COVID-19 pandemic, Ukrainian-Russian conflict, China-US trade war, and current environmental concerns regarding carbon emissions have all made the semiconductor supply chain (SCSC) more vulnerable. In addition, the uncertainty of global SCSC is increasingly obscured owing to several resilience challenges within the exiting supply chain network. Thus, supply chain resilience issues are becoming popular among researchers and policymakers. Unfortunately, there is a lack of systematic research on evaluation of resilience challenges and mitigation strategies for the global SCSC. Additionally, existing models are incompetent to capture the optimistic and pessimistic views of experts during interaction assessment and mitigation strategy evaluation in an uncertain environment. Hence, this research, for the first time, develops a novel integrated Decomposed Fuzzy Set (DFS)-based Delphi, Weighted Influence Non-linear Gauge System (WINGS), and Quality Function Deployment (QFD) model to identify and assess strength-interaction relationship between resilience challenges and mitigation strategies. The findings demonstrated that out of thirteen resilience challenges, seven were identified as causal group resilience challenges while the remaining six were classified as result group resilience challenges indicating that addressing the causal group resilience challenges may directly influence the mitigation of the result group resilience challenges. According to findings of DFS-WINGS analysis, the resilience challenges “Geopolitical tensions” and “Natural disasters” are the two most priority causal group resilience challenges that can significantly influence the result group system components. Furthermore, the DSF-QFD analysis confirmed that the mitigation strategies “Investing in semiconductor R&D and developing regional semiconductor manufacturing facilities” and “Diversification of key components suppliers and promoting domestic manufacturing” received the highest correlation among the mitigation strategies to address the current resilience issues faced by global SCSC. The study findings make a significant contribution to policymaking. The roles of resilience challenges and importance of mitigation strategies both can be used as benchmarks for the SCSC to make the global SCSC more resilient and sustainable.

An entropy - based fuzzy QFD model on used product remanufacturing design

Compared with new products, consumers put forward higher requirements on remanufactured products. Aimed at effectively transforming customer requirements (CRs) to technical characteristics (TCs) of remanufactured product design, an entropy-based fuzzy quality function deployment (QFD) model is proposed. In this model, triangular fuzzy numbers are suggested to express the vagueness information of CRs first, and then the importance of CRs is determined by an entropy-based algorithm, and the relationship between CRs and TCs is well explained by fuzzy QFD; finally, the importance of TCs is determined to clarify the designing emphasis. A remanufacturing engine is conducted to illuminate the practicability of this model. The results show that “Restorability” and “Reliability” will be treated as the key TCs to control, with the importance degree of 0.16 and 0.15. The entropy-based fuzzy QFD model can also be applied to similar product designs.

Benchmarking the quality improvement strategies of wire arc additive manufacturing process using fuzzy QFD approach

PurposeThe purpose of this paper is to improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.Design/methodology/approachTo overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.FindingsInter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.Originality/valueTo the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

Conceptual design and configurations selection of S/H-UAVs based on Q-Rung Dual Hesitant double layer FQFD

For the conceptual design phase of Unmanned Aerial Vehicles (UAVs), a process for conceptual design and configuration selection of Solar/Hydrogen powered UAVs (S/H-UAVs) is proposed. The design requirements of S/H-UAVs were analyzed firstly. The proposed process used Fuzzy Quality Function Deployment (FQFD) to establish logical and quantitative standards. Moreover, in order to appropriately describe the hesitancy of experts while making decision, it used Q-Rung Dual Hesitant Fuzzy Sets (QRDHFS) to score the correlationships. In addition, a decision-making framework is proposed to perform a logical selection of typical layouts based on defuzzification method and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). The present process has been applied for S/H-UAVs. The resulting set of design requirements consists of three categories: Mission Requirements (MRs), Engineering Characteristics (ECs) and Technical Indicators (TIs). Four typical layouts of S/H-UAVs were sorted and determined. The performance of four typical layouts were evaluated and the Strut-Braced Wing (SBW) with external hydrogen storage was selected as the best layout for S/H-UAVs.

Triangular Fuzzy QFD–MCDM Combination Approach for Green Building Design Scheme Evaluation

The integration of green design into building construction is a necessary process in today’s world to address environmental issues and achieve sustainable development. However, when evaluating green building design schemes, various factors are intertwined with a high degree of complexity and uncertainty. To realise rational decision-making about green building design schemes, this paper first adopts the mixed techniques of triangular fuzzy numbers, quality function deployment, and Best–Worst Method. It aims to analyse the complex factor relationship between customer needs and green building design technical features and to solve the optimal green building design index weight allocation. Next, a hybrid fuzzy multi-criteria decision-making (MCDM) method integrating triangular fuzzy numbers, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, and Grey Correlation (GC) are proposed to evaluate green building design scheme performance. Finally, an example of a green design project for a hotel building is selected for application validation and analysis in comparison with the existing Complex Proportional Assessment, VlseKriterijuska Optimizacija I Komoromisno Resenje, and DEMATEL-ANP methods. These analyses demonstrate the stability and validity of the results, as well as the rationality and practicability of the proposed triangular fuzzy QFD–MCDM method. This research is a guide to the problem of evaluating green building design schemes.

Modular design of smart home under the concept of whole-house customization integration

Abstract Digital empowerment of home product design and manufacturing integration, to achieve the whole process of personalized customization of home products innovative design. Using big data for user analysis, we obtained functional demand data for smart home modules, and 28.5% of user demand is reflected in cell phone interconnection. Using the KANO model, user customization demands can be calculated to form basic and excitement type demand expectations represented by A and M. Then based on the fuzzy QFD method for demand raw data conversion, to get the initial weights and weighted weights of each demand item, taking A14 home space utilization efficiency as an example, the initial weights and weighted weights of A14 are 0.66 and 0.10, respectively, and the importance of demand sorted seventh. Combined with the specific application of modular design in smart homes, the modular design of smart homes is verified. Further adjustments should be made to enhance the innovation degree of smart homes.

Engineering equipment conceptual design methodology: using function units configuration and schemes iterative solution

Engineering equipment can efficiently assist humans in completing engineering projects and reduce work intensity. As the difficulty and scope of operations increase, higher requirements are placed on function and integration. In product design, excessive user requirements and design constraints lead to discrete results, difficult to converge. Under multi-functionality and high integration constraints, traditional mapping sub-functions to structures one by one results in overabundant mappings, and discrete, redundant structures after mapping, poorly achieving integration and reducing subsequent iteration efficiency. To address these issues, this paper proposes a conceptual design methodology for engineering equipment with function units configuration and schemes iterative solution. First, the Fuzzy Quality Function Deployment (FQFD) method applies fuzzy theory to requirement-to-function conversion, overcoming ambiguity and subjectivity of user requirements. Second, with the goal of integrated structures, an improved FBS method, i.e. Function-Function Units-Structure (FFUS), aggregates sub-functions after decomposition into function units, and then maps to structures, improving engineering equipment integration. Moreover, the Interactive Genetic Algorithm (IGA) method involves users in an interactive process to generate an optimised design scheme, overcoming blind solution generation. Prototype design and simulation of 8VN1 Gas Insulated Switchgear (GIS) handing equipment demonstrate that the methodologies are effective in aiding engineering equipment conceptual design.

A Multi-stage Optimization Strategy Based on Fuzzy QFD and Fuzzy Swara to Adopt Blockchain Technology in the Drug Supply Chain

Introduction: Utilizing blockchain technology helps to address issues that the supply chain faces, including the intricate connections between chain network members, regulation of the distribution network, and inventory management.
 Objective: To adopt blockchain technology in the drug supply chain, this study aims to offer a multi-stage optimization strategy based on Swara and QFD approaches and a zero-one nonlinear optimization problem employing a fuzzy approach.
 Methods: First, field and library research was conducted to identify the barriers to the adoption of blockchain technology in the drug supply chain and the ways to overcome these barriers. The relevance of the barriers is ascertained using the fuzzy Swara approach following their refinement employing the Friedman test. The output is entered as an input in the house of quality (HOQ) rows, while the barrier-reducing techniques are presented in the columns. These approaches to reducing barriers are arranged in rows in the second phase of the house of quality.
 Results: Among the criteria of the barrier-reduction approach, the Performance Expectancy criterion with a score of 0.0521 has the greatest score, and the criterion of Focusing on the Major Points has the minimum score, as determined by the findings of the fuzzy Swara model. The criterion of Enhancing Transparency with a score of 0.5374 and Reducing Risk with a score of 0.4045 have the maximum, and Sustainability Performance with a score of 0.07 has the minimum score, according to the findings concerning the objectives of blockchain technology adoption in the drug supply chain. The criterion of lack of customers' awareness and attitude about sustainability and blockchain technology has the greatest score among the barriers to adoption, scoring 0.521, and the criterion of difficulty in altering organizational culture, scoring 0.033, has the minimum value.
 Conclusion: Based on the results of the fuzzy house of quality, we concluded that, for the adoption of blockchain technology in the drug supply chain, the eighth (long-term perspective), first (performance expectation), and tenth (focused on the primary strengths) strategies are more beneficial. In addition, it was demonstrated that the second (Effort Expectation), ninth (information sharing), and sixth (Trust) strategies have poor rankings.

Fuzzy QFD for LCC Strategic Decisions in Thailand

This study focuses on the impact of the Covid-19 crisis on low-cost carriers (LCCs), particularly in comparison to full-service airlines (FSAs). With a target segment of price-sensitive leisure travelers, LCCs have been significantly affected. The objective of this paper is to analyze customer requirements for Thai LCCs during the Covid-19 recovery period and identify strategic improvement decisions accordingly. Nok Air, a well-established LCC in Thailand, is used as a case study. The proposed fuzzy QFD approach is employed to prioritize customer requirements, suggest strategic decisions, and enhance operational practices for the airline's recovery. Key findings include positioning as a premium LCC, offering premium services, increasing ancillary revenue, and improving aircraft utilization. This research is the first to apply fuzzy QFD to prioritize strategic decisions for managing LCCs during the Covid-19 recovery, aiming to enhance customer satisfaction and performance ratings set by the management team.

Retracted: Rational Supplier Selection Based on Two-Phase Deep Analysis considering Fuzzy QFD and Game Theory

Retracted: Rational Supplier Selection Based on Two-Phase Deep Analysis considering Fuzzy QFD and Game Theory

Providing a Framework for Performance Evaluation of Organizations in Successfully Implementing TQM, Based on Knowledge Management Approach and Organizational Agility

Nowadays, any organization, in order to be aware of the desirability and quality of its activities, especially in dynamic environments, urgently needs an evaluation system to assess its system’s performance and efficiency. In this study, the performance of production and service organizations has been evaluated according to the effect of knowledge management success factors and organizational agility on the success factors of total quality management (TQM (total quality management)). Considering that the two areas of knowledge management and organizational agility are among those influential on TQM and each has been examined separately in the previous studies in relation to it, none of the previous studies has focused on all these three areas together. Therefore, in the present study, in addition to evaluating the performance of organizations based on the success factors of TQM, we seek to identify the influential factors and success factors of each of the three areas of knowledge management, organizational agility, and TQM; then, the impact of knowledge management and organizational agility on the success factors of TQM is evaluated. To express the above-given relationship, group interpretive structural modelling (ISM (interpretive structural modelling)) techniques have been used to rank the components of each domain; also, fuzzy quality function deployment (FQFD (fuzzy quality function deployment)) technique has been applied to find the weight and relationship of the three mentioned domains by examining the independent and interface variables of the previous step. The weights resulting from two-stage house of quality have been used as the weights for the design of the two-stage data envelope analysis (DEA) model by the weight control method. Finally, the above-given factors in knowledge-based companies located in Khorramabad Science and Technology Park have been studied and the results have been expressed.

Improving School Reconstruction Projects Satisfaction Outcomes Using Fuzzy Quality Function Deployment (FQFD)

School buildings and facilities constitute essential educational infrastructure and have a formative impact on the safety, development, and socialization of students. However, many existing school buildings are increasingly aging and deteriorating, requiring urgent refurbishment, raising the need to assess and develop a quality function to propose strategies for improved school building reconstruction. Apart from the initial planning phase, the reconstruction design process usually requires detailed information regarding owner/user demands and is often presented in terms of user dissatisfaction. This paper applies fuzzy quality function deployment (FQFD) to transform actual user needs into an improved technical strategy that can be realized by the design unit through the sequence of the matrix method. The resulting framework identifies a total of eight major components of user dissatisfaction, along with three key school-design improvement strategies, including the use of environmentally sound materials, overall quality of design and planning, and playground planning. In terms of technology improvement strategies, the prioritized design improvement strategies for increasing school reconstruction satisfaction include considerations of practicality and constructability, planning use points and maintenance methods, designing the site according to the local terrain, and using materials that match the layout of the environment. The approach proposed in this study can be used to enhance the efficiency of the reconstruction of aging buildings and the research results can also augment ontological knowledge on the reconstruction of aging campus buildings.

Decision support for technology transfer using fuzzy quality function deployment and a fuzzy inference system

Technology transfer plays an essential role in developing an organization’s capabilities to perform better in the market. Several protocols are defined for technology transfer. One of the main techniques in technology transfer is licensing, which significantly impacts profit and income. This study intends to develop a decision framework that integrates both a Fuzzy Inference System (FIS) and a two steps Fuzzy Quality Function Deployment (F-QFD) to assist an organization in selecting a licensor. To illustrate the decision framework’s performance, it has been implemented in an Iranian lubricant producer to select the best licensor among the 13 targeted companies. A complete product portfolio, brand image enhancement, increasing the market share of the high-value products, and improving the technical knowledge of manufacturing products were identified as the most important expectations of the licensees. A sensitivity analysis for the recommended framework has been conducted. For doing so, 27 rules of the FIS were categorized into four group and then changed. The results are compared using the Pearson correlation coefficient. Inference rules detect unconventional changes, while logical changes are appropriately considered.

A sustainable and resilient supply chain (RS-SCM) by using synchronisation and load-sharing approach: application in the oil and gas refinery

Nowadays sustainable and resilient supply chain management (R&S-SCM) is an interesting and in the meantime vital problem that has grabbed the attention of many researchers. This study is an effort to investigate the simultaneous design of sustainable and resilient flow in the supply chain. To achieve a sustainable and resilient supply chain, there is a wide variety of strategies depending on their impacts on different industries and the features of their supply chain. The fuzzy QFD method is designed to select the most appropriate strategy in the study. Two approaches are used for this purpose. Early planning in sustainable mode is formulated assuming that all members of the network are healthy and final planning in the reactive approach to destruction which formulates the return to the original state in the shortest possible time, cost and scenario-based status. A hybrid priority-based Genetic Algorithm (pb-GA) and simulated annealing algorithm (SA) is developed in two phases to find the optimal solutions. Response Surface Methodology (RSM) method is used to adjust significant parameters for the algorithm. Several test problems are generated showing that the proposed metaheuristic algorithm can find good solutions in reasonable time spans.

Identification of Retailer Needs for Influential Logistics Activities in the Implementation of Halal Logistics for Perfume Products Using the Fuzzy QFD (Quality Function Deployment) Method

Determining the needs of retailers in implementing halal logistics can be identified using the Fuzzy QFD (Quality Function Deployment) method. Assessment of retailer needs was carried out by 3 sources. Then the results of the assessment are translated into Fuzzy numbers and then the HOQ matrix is designed. Based on the research conducted, obtained 7 retailer needs and 13 technical characteristics that influence the implementation of halal logistics. Then from 4 kinds of levels of relationship between each technical characteristic, 2 kinds of assessments were obtained, namely the level of strong positive and weak positive relationships. Assessment of the strength of the relationship between each retailer's needs and logistics activities in the context of implementing the halal logistics system for the value of the "Very Strong" relationship can be seen in the relationship between special packaging and ordering costs and special packaging with guaranteed goods condition. As for the value of the strength of the "Medium" relationship, it can be seen in the relationship between the concoction according to the wishes of consumers with the ordering fee and the halal guarantee fee with the ordering fee.

Combining GRA with a Fuzzy QFD Model for the New Product Design and Development of Wickerwork Lamps

With the popularization of the concept of sustainability in traditional wickerwork, wickerwork lamps have become the most popular production. When customers purchase wickerwork lamp products, the Kansei consensus has become a key factor influencing the communication between manufacturers and customers. Therefore, the purpose of this paper is to explore the product design solutions for wickerwork lamps that meet the emotional satisfaction of users. Firstly, a three-level evaluation grid diagram driven by user attractiveness through Miryoku Engineering is established. Secondly, this paper uses grey relational analysis (GRA) to extract the priority order and its weight values in the perceptual vocabulary to identify the key user needs in product design. In order to effectively deal with the uncertain product evaluation information, the fuzzy quality function deployment (QFD) is used to construct the “emotional demand-design parameter” transformation model and derive the optimal design parameters in the mapping process, thus effectively reducing the ambiguity and uncertainty in the demand transformation process. Based on the experimental results, it is found that the best combination of Texture light transmittance, Simple wickerwork material, Wickerwork primary colours, Cascaded type and Pastoral style could be preferred by customers, thus this proposed method can effectively reduce the ambiguity and uncertainty in the design process. The results of study enable designers to accurately grasp customers’ perceptions of wickerwork lamp products and obtain the best design parameters for wickerwork lamp products.

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

PurposeSupplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).Design/methodology/approachThe proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.FindingsA fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.Originality/valueQFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

Integrating continuous fuzzy Kano model and fuzzy quality function deployment to the sustainable design of hybrid electric vehicle

Integrating continuous fuzzy Kano model and fuzzy quality function deployment to the sustainable design of hybrid electric vehicle

An analysis of the literature on the use of Fuzzy QFD in logistics strategies

An analysis of the literature on the use of Fuzzy QFD in logistics strategies