Integrating Quality Function Deployment with Fuzzy Cognitive Maps for Resolving Correlation Issues in the Roof Matrix

Quality function deployment (QFD) is a systematic approach that captures customer requirements and translates them, through house of quality (HOQ), into engineering characteristics of product. As the functional relationships between customer requirements and engineering characteristics in QFD are uncertain, unclear and fuzzy, radial basis function (RBF) to determine the functional relationships for QFD is presented, and a QFD functional relationships model based on RBF is proposed. According to RBF neural network can realize the nonlinear mapping space from the input space to the output, and can obtain the optimal relationships pattern of the input and output, the customer requirements and engineering characteristics in QFD constituted the input and output of the RBF neural network respectively, the optimal relationships are constructed through the neural network training. A case study of natural lighting products development is provided to illustrate the application of the presented method.

As a useful product development technique, quality function deployment (QFD) can convert customer requirements into suitable engineering characteristics for maximum customer satisfaction. Nonetheless, the traditional QFD has been extensively criticized as having many defects in practical applications, which include the crisp evaluation of relationships between customer requirements and engineering characteristics, and the non-robust ranking of engineering characteristics. In this paper, we put forward a new method using double hierarchy hesitant linguistic term sets (DHHLTSs) and axiomatic design approach to enhance the performance of the classical QFD. Firs, the DHHLTSs are employed to evaluate the relationships between customer requirements and engineering characteristics. Then, the axiomatic design theory is extended to derive the prioritization of engineering characteristics in QFD. Additionally, a maximizing consensus method is used to determine the weights of experts considering inconsistency among their opinions. Finally, an empirical case of a shared car manufacturer is provided with a comparison analysis to demonstrate the feasibility and effectiveness of our proposed QFD approach.

PurposeThe concept of sustainable product design (SPD) is gaining significant attention in recent research. However, due to inherent uncertainties associated with new product development and incorporation of multiple qualitative and quantitative criteria; SPD is a complex and challenging task. The purpose of this paper is to introduce a novel approach by integrating quality function deployment (QFD), multi-criteria decision making (MCDM) technique and Six Sigma evaluation for facilitating SPD in the context of Industry 4.0.Design/methodology/approachThe customer requirements are evaluated through the neutrosophic-decision-making trial and evaluation laboratory-analytic network process (DEMATEL-ANP)-based approach followed by utilizing QFD matrix to estimate the weights of the engineering characteristics (EC). The Six Sigma method is then employed to evaluate the alternatives’ design based on the ECs’ values.FindingsThe effectiveness of the suggested approach is illustrated through an example. The result indicates that utilization of the neutrosophic MCDM technique with integration of Six Sigma methodology provides a simple, effective and computationally inexpensive method for SPD.Practical implicationsThe proposed approach is helpful in upstream evaluation of the product design with limited experimental/numerical data, maintaining a strong competitive position in the market and enhancing customer satisfaction.Originality/valueThis work provides a novel approach to objectively quantify performance of SPD under the paradigm of Industry 4.0 using the integration of QFD-based hybrid MCDM with Six Sigma method.

Quality function deployment (QFD) is a proven useful methodology in new product development to satisfy customer requirements (CRs). House of quality (HoQ), the general implementing mode of QFD, is aimed to identify the variables of engineering characteristics (ECs) based on the relationships between CRs and ECs. Traditionally, the establishment of these relationships is mainly dependent on the designers' experience and then the HoQ included many items difficult to handle. For aiding the designers on the HoQ analysis, the paper proposes an Apriori-based data mining approach to extract knowledge from historical data. The approach is mainly focused on mining potential useful association rules (including positive and negative rules) that reflect the relationships according to three objectives: support, confidence, and interestingness. For ensuring the availability and conciseness of these extracted rules, the definitions and calculations of rule conflict and redundancy are proposed and processing procedures are also developed to unite or delete unnecessary rules. The reserved rules are clustered in order to facilitate rule management and reuse. Furthermore, a reuse procedure is also developed for new HoQ analysis. Computational experiments of an electrically powered bicycle are used to illustrate the proposed approach and its capability of extracting useful knowledge.

Quality function deployment (QFD) is a systematic approach to transform customer requirements (CRs) into product engineering characteristics (ECs). Traditional QFD relies on market research or customer questionnaires to collect a series of ambiguous and uncertain CRs. As a result, evaluating the weighting of CRs and determining the design matrix between CRs and ECs have become the focus and difficulty of QFD. This paper proposes the grey system theory in artificial intelligence technology combined with QFD to develop grey-QFD to solve the issues mentioned before. First, collect the average evaluation values between the aesthetic images and customer satisfaction of representative products. The grey prediction GM (1, N) model is used to obtain the weight of aesthetic needs relative to customer satisfaction and import it into the left QFD. Second, the domain experts decomposed the product form into a morphological analysis table, and fuzzy Delphi screened key ECs and imported them into the ceiling of QFD. Finally, grey relationship analysis established the aesthetic product design matrix between CRs and ECs, and calculated and ranked the final weights of each ECs by using grey relationship degree. The research uses the security camera in the smart home as an experimental object. After operating the proposed grey-QFD, the aesthetic quality of the target product (lively, intelligent, friendly, personalized, and fashionable) and the optimization of the corresponding product ECs are obtained. The result provides a theoretical reference for designers and significantly improves customer aesthetic satisfaction.

Purpose – The purpose of this paper is to report a case study in which financial feasibility integrated quality function deployment (QFD) approach was implemented. Design/methodology/approach – Customer complaints were systematically gathered. The house of quality (HoQ) matrix was developed. The technical descriptors were prioritized and subjected to the financial feasibility study. The cost calculations were carried out and the actions were derived. A set of value engineering (VE) principles was used during this case study. Findings – The study reported in this paper indicated the need for integrating financial feasibility study with QFD for enhancing the effectiveness of the method. The measures taken to prevent the customer complaints will be of considerable value to the manufacturing organizations. Research limitations/implications – During the conduct of case study, high-cost factors restricted the selection of materials which would exhibit higher performance. The case study was carried out in a single electronic switches manufacturing organization. Practical implications – The manufacturing costs incurred have been reduced by incorporating changes in the part material. The outcomes of the study have been considered for further implementation in the case organisation which indicated the practicality of the study. Originality/value – The concept of apportionment of HoQ cost developed with the idea of integrating the same with QFD is the original contribution of the authors.

Quality function deployment (QFD) is a planning and problem-solving tool that is gaining acceptance for translating customer requirements into the engineering characteristics of a product. Deriving the rating order of engineering characteristics from input variables is a crucial step in applying QFD. A grey method is proposed to prioritize engineering characteristics. The engineering characteristics are considered to be comparability sequences, while the customer requirements in customer competitive analysis are considered to be reference sequences. So QFD can be regarded as a grey system and the relationships between the customer requirements and engineering characteristic can be determined with the grey relational matrix. Then grey superior analysis is used to prioritize the engineering characteristics. An example of the door design of an automobile is used to demonstrate the application of the proposed approach.

PurposeThe purpose of this paper is to apply a fuzzy LinPreRa cognitive map to evaluate the interaction and importance of factors affecting the development of strategic alliance partnerships between the outlying island duty-free shops and existing collaboration firms in duty-free shops. Meanwhile, the key factors should be considered in establishing strategic alliance partnerships while analyzing and comparing the perspectives of owners for outlying island duty-free shop and partner vendors of collaborating firms along with differences of influencing key factors on partnership quality.Design/methodology/approachThis study incorporates a fuzzy linguistic preference relation analytical network process (fuzzy LinPreRa ANP) in the fuzzy cognitive map (FCM) method to formulate a fuzzy LinPreRa cognitive map to evaluate the interactions and importance of key factors and the conditions of interactive impacts during the establishment of strategic alliance partnerships. The authors use the outlying island duty-free shops in Taiwan as the empirical subject to illustrate how the fuzzy LinPreRa cognitive map is applied. In-depth, interviews and questionnaire surveys are conducted to collect and evaluate respondents concerning key factors affecting strategic alliance partnerships establishment.FindingsThe following three findings based on the results of empirical analysis: first, the administrative behavioral patterns of managers for strategic alliance partnerships encompass shared values and goal coherence, while the associative statements are located on the first layer of fuzzy LinPreRa cognitive map core associations, which illustrates that businesses attach great importance to conceptual ideas. Second, integrity and reputations of both parties are the governing mechanism of strategic alliance partnerships, influencing mutual reputation. Third, the relationship of strategic alliance partnerships refers to the profit opportunities of both parties and their ability to respond to the market, including future development, regional indicators, marketing capabilities, brand multiplicity and customer retention. However, it can be inferred that such associative factors are located in the outer layer or belong to noncore associations, which means that both parties’ abilities to respond to market reactions are weakened.Practical implicationsThis study provides valuable relationship managerial strategies to maintain long-term partnerships for outlying island duty-free shops and their alliance collaborating firms including strengthened relationships of both parties’ managers to achieve common values and consistent objectives; improved beneficial value of both parties in strategic alliance partnerships; continued close communications to enhance the quality of strategic alliance partnerships; and establishment of personnel training mechanisms and strict formulation of management rules for strategic alliance partnerships.Originality/valueThe main valuable contributions are included the fuzzy LinPreRa cognitive map by combining two different decision methods including FCM and fuzzy LinPreRa ANP is proposed to help decision makers to improve the evaluation quality and calculation efficiency for critical elements’ interaction and importance; the fuzzy LinPreRa cognitive map can clarify considering significant factors when maintaining strategic alliance partnerships and further provide valuable relationship managerial strategies to maintain long-term relationships for duty-free shop owners and their alliance collaborating firms.

The success of a new product is usually determined not by whether it includes high-end technology, but by whether it meets consumer expectations, especially key Kansei demands. This article aims to evaluate attractive factors (Kansei words) and convert them to design elements to make products stand out in the global competition. The evaluation grid method (EGM) is an important research method of Miryoku engineering. The method can build qualitative relations among consumers’ attractive factors and design elements. The quality function deployment (QFD) is a quantitative method which converts customer requirements into engineering characteristics using the House of Quality Matrix. The QFD together with the concept of fuzziness can objectively measure questionnaires made by experts. Accordingly, this paper proposes a systematic approach that integrates the EGM together with the fuzzy QFD for the development of new products. The fuzzy Kano model combined with the fuzzy analytic hierarchy process (AHP) is developed to determine the priority of the development of attractive factors. This empirical study uses minicars as an example to verify the feasibility and validity of the approach. The results are expected to help designers to increase design efficiency and improve consumer satisfaction of new products.

Quality is the ability of a product to meet or exceed customer expectations. Quality function deployment is a product development process based on the notion of House of Quality (HOQ). HOQ is a design approach to translate customer’s expectations into engineering characteristics so that the customer’s expectations can be met. The reduction of variability in important quality characteristics leads to better product quality. Taguchi method focuses on the variability of important quality characteristics. Two key concepts or techniques with the Taguchi method are quality loss and robust design by experimental optimization. This chapter introduces all these design techniques for quality, including the model-based optimum method.

Quality function deployment (QFD) is becoming a widely used customer-driven approach and tool in product design. The inherent fuzziness in QFD modelling makes fuzzy regression more appealing than classical statistical tools. A new fuzzy regression-based mathematical programming approach for QFD product planning is presented. First, fuzzy regression theories with symmetric and non-symmetric triangular fuzzy coefficients are discussed to identify the relational functions between engineering characteristics and customer requirements and among engineering characteristics. By embedding the relational functions obtained by fuzzy regression, a mathematical programming model is developed to determine targets of engineering characteristics, taking into consideration the fuzziness, financial factors and customer expectations among the competitors in product development process. The proposed modelling approach can help design team assess relational functions in QFD effectively and reconcile tradeoffs among the various degree of customer satisfaction and determine a set of the level of attainment of engineering characteristics for the new/improved product towards a higher customer expectation within design budget. The comparison results under symmetric and non-symmetric cases and the simulation analysis are made when the approach is applied to a quality improvement problem for an emulsification dynamite packing machine.

An FCM–FAHP approach for managing readiness-relevant activities for ERP implementation

Krepek tette is one of the traditional chips from Pamekasan. Generally, this product is a famous souvenir from the city. This product is usually produced by a small-medium enterprise (SME). In the krepek tette industry, the steaming process is dependent on wood as fuel. The condition makes the steaming process contributes significantly to the resulting carbon footprint. To support sustainable development goals (SDGs), explicitly ensuring sustainable consumption and production pattern. The production process technology in SMEs needs to be upgraded to achieve sustainable production. One of the solutions is to re-design the steamer for the steaming process of raw cassava. To achieve a good steamer design, gathering information about customer need is a fundamental step to accomplish. The research aims to investigate criteria steamer design that meets customer needs. The survey gathered data about customer requirements and pointed to employees in the krepek tette industry located in central production, Blumbungan sub-district, Pamekasan. All qualitative data were analyzed using fuzzy logic to quantify the value of customer requirements and engineering characteristics. House of Quality, the first matrix of QFD, was used to obtain engineering characteristics priority. There was 12 attribute of customer requirements; however, one attribute failed to meet minimum customer importance weight criteria. Translating customer requirements to engineering characteristics obtain ten attributes. Using fuzzy logic to rank engineering characteristics that meet customer requirements, obtain eight attributes for the design criteria of cassava steamer. The attributes were ignition system used heat element, stainless steel, the design used modular systems, used LPG fuel, input, and output process from the same side, temperature and steam disperse equally, and used under steam pressure

In this paper, an approach combining the Kano model and quality function deployment (QFD) is proposed to meet customer requirements in product design. The Kano model provides an effective way to categorizing customer requirements and helps understand the nature of these requirements. The Kano model categories the customer satisfaction into three fields, namely, must be, attractive and exciting. QFD is a customer-focused product design method. It can transfer customer requirements to products' engineering characteristics. By combining the two methods, we can provide a new way to optimize the product design. The proposed methods can be useful to both practitioners and researchers.

As a powerful tool for improving customer satisfaction, quality function deployment (QFD) can convert customer requirements (CRs) into engineering characteristics (ECs) during product development and design. Aiming to address the deficiencies of traditional QFD in expert evaluation, CRs’ weight determination and ECs’ importance ranking, this paper proposes an enhanced QFD model that integrates hesitant fuzzy binary semantic variables, the Best–Worst Method (BWM), and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The objective is to determine the prioritization of product engineering characteristics. Indeed, hesitant fuzzy linguistic term sets (HFLTS) have found extensive application in decision-making problems. Compared to other fuzzy language methods, HFLTS offers greater convenience and flexibility in addressing decision-makers’ hesitations and uncertainties. Initially, the combination of hesitant fuzzy linguistic term sets with interval binary tuple language variables is employed to articulate the uncertainty in the assessment information provided by QFD team members. Subsequently, the improved BWM and TOPSIS methods based on HFLTS are used to improve the accuracy of the importance ranking of engineering characteristics by determining the weights of CRs and prioritizing ECs in two stages. Finally, the feasibility and effectiveness of the proposed method are validated through an illustrative example.