The implementation of quality function deployment based on linguistic data

Quality function deployment (QFD) is a customer-driven quality management and product development system for achieving higher customer satisfaction. The QFD process involves various inputs in the form of linguistic data, e.g., human perception, judgment, and evaluation on importance or relationship strength. Such data are usually ambiguous and uncertain. An aim of this paper is to examine the implementation of QFD under a fuzzy environment and to develop corresponding procedures to deal with the fuzzy data. It presented a process model using linguistic variables, fuzzy arithmetic, and defuzzification techniques. Based on an example, this paper further examined the sensitivity of the ranking of technical characteristics to the defuzzification strategy and the degree of fuzziness of fuzzy numbers. Results indicated that selection of the defuzzification strategy and membership function are important. This proposed fuzzy approach allows QFD users to avoid subjective and arbitrary quantification of linguistic data. The paper also presents a scheme to represent and interprete the results.     

Fuzzy cognitive map based quality function deployment approach for dishwasher machine selection

The traditional quality function deployment (QFD) approach deals with the weights of customer requirements (CRs), relationships among CRs and design requirements (DRs), correlation among DRs by using crisp values. This paper uses fuzzy numbers to improve the drawbacks of the traditional QFD method because fuzzy numbers enable to make consistent decisions in uncertain environment to decision makers. The existing papers handle a simple multiplication operation to calculate the correlation among CRs and the correlation among DRs. This study proposes fuzzy cognitive map (FCM) approach to calculate these correlations so that FCM is a successful method to handle the interactions among criteria. This paper contributes to the literature by integrating QFD approach and fuzzy cognitive map approach. The weights of DRs are defined in the result of the proposed QFD approach. These weights are used to evaluate the dishwasher machine alternatives in intuitionistic fuzzy VIKOR method. Intuitionistic fuzzy number (IFS) ensures to handle more information than type-1 fuzzy number to describe the fuzziness and the uncertainty of the real life world. Finally, the proposed approach has been implemented to a dishwasher machine selection in order to test its validity.     

Managing software requirements using quality function deployment

In this article we describe and discuss QFD (quality function deployment) as a framework for managing software requirements. Experiences were gained while participating as researchers in a commercial large-scale software telecommunications project at Ericsson Radio Systems AB. We found that prerequisites for succeeding with QFD include having visible customers and users, forming a cross-functional team adequately trained in QFD, and allowing adequate time for its first application. Advantages of using QFD are: better focus on customers and users, an effective means of prioritizing and communicating software requirements; and managing non-functional requirements. Issues not fully supported by QFD include adequate abstractions levels in describing requirements, handling temporal relations between requirements and initiating the use of QFD for a new development project.     

Using integrated quality function deployment and theory of innovation problem solving approach for ergonomic product design

A multidisciplinary approach integrating method of identification of customer satisfaction needs (CSNs), the House of Quality (HoQ) chart of quality function deployment (QFD), theory of innovation problem solving (TRIZ) and fuzzy group decision-making theory for ergonomic product innovative design and evaluation in the early design stages was proposed. An integrated model and the approach procedures consists of four steps. In step 1, identification of CSNs is based on a data source triangulation approach, questionnaire survey, 5-point liner numeric rating scale, factor analysis, and Cronbach’s coefficient alpha statistic are utilized to guarantee that the CSNs are complete and reliable. In step 2, a correlation matrix is built to identify the critical ergonomic design areas and the key problems are established by analysis of the negative relationships obtained from interrelationship half-matrix at the roof of the HoQ. In step 3, to solve the problems, TRIZ main tools and contradiction analysis are utilized. Several innovative alternatives are generated by combining appropriate Inventive Principles of TRIZ, the critical ergonomic design areas and the ergonomic design principles. In step 4, a general and easy fuzzy group decision-making method for evaluating of the best design alternatives is presented. A case study of the integrated kitchen stove innovative design and evaluation is conducted to demonstrate the applicability of the proposed approach.     

A quantitative approach for setting technical targets based on impact analysis in software quality function deployment (SQFD)

Target setting in software quality function deployment (SQFD) is very important since it is directly related to development of high quality products with high customer satisfaction. However target setting is usually done subjectively in practice, which is not scientific. Two quantitative approaches for setting target values: benchmarking and primitive linear regression have been developed and applied in the past to overcome this problem (Akao and Yoji, 1990). But these approaches cannot be used to assess the impact of unachieved targets on satisfaction of customers for customer requirements. In addition, both of them are based on linear regression and not very practical in many applications. In this paper, we present an innovative quantitative method of setting technical targets in SQFD to enable analysis of impact of unachieved target values on customer satisfaction. It is based on assessment of impact of technical attributes on satisfaction of customer requirements. In addition both linear and non linear regression techniques are utilized in our method, which certainly improves the existing quantitative methods which are based on only linear regression. Frank Liu is currently an associate professor and a director of the McDonnel Douglass Foundation software engineering laboratory in the University of Missouri-Rolla. He has been working on requirements engineering, software quality management, and knowledge based software engineering since 1992. He has published about 50 papers in peer-reviewed journals and conferences in the above areas and several other software engineering application areas. He participates in research projects with a total amount of funds of more than four millions dollars as a PI or Co-PI sponsored by the National Science Foundation, Sandia National Laboratory, U.S. Air Force, University of Missouri Research Board, and Toshiba Corporation. He has served as a program committee member for many conferences. He was a program committee vice chair for the 2000 International Conference on Software Engineering and Knowledge Engineering. Kunio Noguchi is a senior quality expert in the software engineering center in the Toshiba Corporation. He has published several papers in the area of quality management systems. Anuj Dhungana was a M.S. graduate student in the computer science department at the Texas Tech University when he performed this research. V.V.N.S.N. Srirangam A. was a M.S. graduate student in the computer science department at the Texas Tech University when he performed this research. Praveen Inuganti was a M.S. graduate student in the computer science department at the University of Missouri-Rolla when he performed this research.     

A linear goal programming approach to determining the relative importance weights of customer requirements in quality function deployment

Quality function deployment (QFD) is a planning tool used in new product development and quality management. It aims at achieving maximum customer satisfaction by listening to the voice of customers. To implement QFD, customer requirements (CRs) should be identified and assessed first. The current paper proposes a linear goal programming (LGP) approach to assess the relative importance weights of CRs. The LGP approach enables customers to express their preferences on the relative importance weights of CRs in their preferred or familiar formats, which may differ from one customer to another but have no need to be transformed into the same format, thus avoiding information loss or distortion. A numerical example is tested with the LGP approach to demonstrate its validity, effectiveness and potential applications in QFD practice.     

Routine design with information content and fuzzy quality function deployment

Design can be classified into four basic categories: creative design, innovative design, redesign, and routine design. This paper describes a method for performing routine design by utilizing information content and fuzzy quality function deployment. An attempt has been made to associate with each critical characteristic of a product a value representing the information content, which is a measure of probability that a system can produce the parts as specified by the designer, using a specific manufacturing technology for making the parts. Once the information content of each design alternative is computed, the system will select an alternative with the minimum amount of information content. The proposed method provides us with a means for solving the critical design evaluation and validation problem.     

A new integrated approach for engineering characteristic prioritization in quality function deployment

As a customer-driven quality improvement tool, quality function deployment (QFD) can convert customer requirements (CRs) into appropriate engineering characteristics (ECs) in product design and development. However, the conventional QFD method has been criticized for a variety of drawbacks, which limit its efficiency and potential applications. In this study, a new QFD approach integrating picture fuzzy linguistic sets (PFLSs) and the evaluation based on distance from average solution (EDAS) method is proposed for the determination of ranking order of ECs. The PFLSs are utilized to express the judgements of experts on the relationships among CRs and ECs. Then, the EDAS method is extended under picture fuzzy linguistic environment for the prioritization of the ECs identified in QFD. Moreover, a combined weighing method based on technique for order of preference by similarity to ideal solution (TOPSIS) and maximum entropy theory is established to calculate the weights of experts objectively. Finally, a product-service system design is provided to illustrate the effectiveness of the proposed QFD approach. The result shows that the manufacturer should pay more attention to “Meantime before failure”, “Warning feature” and “Quality of product manual”. Feedback from domain experts indicates that the integrated approach being proposed in this paper is more suitable for assessing and prioritizing ECs in QFD.     

Quality function deployment implementation based on Fuzzy Kano model: An application in PLM system

Product lifecycle management (PLM), a strategic business system allows more effective communication among different groups at dispersed locations to share ideas and access information needed for developing new products and executing innovative processes. The main function of PLM is to develop an attractive system which ensures customer satisfaction. Therefore, one of the important topics of the PLM system developments is to take customer requirements into consideration. Quality function deployment (QFD) has been widely used for numerous years; it is one of the structured methodologies that are used to translate customer needs into specific quality development. However, in the traditional QFD approach, each element’s interdependence and customer requirements are usually not systematically treated. Additionally, the Kano model can effectively classify customer demand attributes, but to make Kano model more objective in the course of weighing, we have also included Fuzzy mode in our discussion. This study presents an integrative approach by incorporating the Kano model with Fuzzy mode into the matrix of QFD and adjusting customer requirement weights. This approach can fulfill two objectives, First, through the Kano model with the Fuzzy mode, it will not only discriminate out options for the required attributes in much more breadth but also simultaneously render the discretions on the linguistic implications much more accurate with the aid of the ambiguous questionnaire response method. Second, combining the Kano model and QFD, can not only provide a new way to optimize the product design but can also enhance customer satisfaction and loyalty, and minimize dissatisfaction. The proposed methods can be useful to both practitioners and researchers. To illustrate our findings, we have incorporated an example which suggests that the proposed approach can contribute to the creation of attractive PLM attributes and PLM innovation.     

Synchronous quality function deployment (QFD) over world wide web

Quality function deployment (QFD) is one of the formal techniques for effective product development. Its main purpose is to listen to the voice of the customer and deploy it down the stream of product development with minimum loss or distortion. It achieves this purpose by using a series of matrices. QFD is a team tool. However, most of computerized QFD systems are standalone and therefore offer limited support for teamwork. This paper proposes to employ the world wide web (WWW, web) technology to provide QFD services on the Internet/Intranets. The synchronized collaboration between team members distributed geographically and over time is particularly emphasized in this development. The resulting web-based QFD system requires no installation or maintenance on the client side but offers remote and simultaneous accesses and therefore supports better teamwork.     

A methodology of determining aggregated importance of engineering characteristics in QFD

Quality function deployment (QFD) is a planning and problem-solving tool that is gaining acceptance for translating customer requirements (CRs) into engineering characteristics (ECs) of a product. Deriving the importance of ECs is a crucial step of applying QFD. However, the inherent fuzziness in QFD presents a special challenge to effectively evaluate the importance of ECs and correlation among them. Furthermore, degree of impact of an engineering characteristic (EC) on the other ECs also reflects the importance of the ECs. In previous studies, those impacts were neglected or simply represented using a linear combination in determining the importance of ECs. To address this issue, in this paper, a new methodology of determining aggregated importance of ECs is presented which involves the consideration of conventional meaning of importance of ECs as well as the impacts of an EC on other ECs. In the proposed methodology, fuzzy relation measures between CRs and ECs as well as fuzzy correlation measures among ECs are determined based on fuzzy expert systems approach. These two types of measures are then used to determine the aggregated importance of ECs. An example of design of a digital camera is used to illustrate the proposed methodology.     

Construction of house of quality for new product planning: A 2-tuple fuzzy linguistic approach

A house of quality (HOQ) diagram is used to analyze the critical factors involved in the quality function deployment (QFD) processes for the new product planning (NPP). The principal tasks of the QFD acting process comprise describing and scoring customer requirements (CRs); determining design requirements (DRs), the relationship between CRs and DRs, the correlations among CRs, and the correlations among DRs. Finally, the DRs can be scored by these assessments in NPP. This study proposes various methods of scoring the requirements of current and potential customers to reflect the knowledge and preference differences among different customers regarding CRs. The CR scores provided by different customers can be assessed by using linguistic, numerical, and interval values, or can be assessed using linguistic label sets with different granularity. A 2-tuple fuzzy linguistic computational approach is adopted to aggregate the CR importance scores obtained from customers by using various methods. In addition, to accurately rate the DRs, a modified relationship between CRs and DRs is proposed. The proposed HOQ construction model is practical because it prevents the loss of information during the QFD process for NPP. An example is used to demonstrate the applicability of the proposed model.     

Research on multi-objective decision-making under cloud platform based on quality function deployment and uncertain linguistic variables

With developments in cloud computing and big data, the term “cloud” has become a household name owing to its characteristics of smartness and connectedness. Cloud-based platforms are associated with people. However, multi-objective decision-making problem in cloud platforms has not been extensively studied. There is no consensus on the reasonable and effective implementation of the decision-making model to select the optimum design scheme in a cloud platform and its establishment to objectively evaluate its significance. In this study, to efficiently and accurately realize the optimal selection of design scheme, a fuzzy evaluation mechanism in handling the vagueness and uncertainty is established, with the advantage of quality function deployment and strength Pareto evolutionary algorithm in decision analysis. A case study is provided to validate the proposed approach in cloud platforms. To reveal the advantages of the proposed method, it was compared with other methods such as the requirement-scenario-experience evaluation framework and a rough number-based integrated method. MATLAB programming was used for this comparison and accuracy certification. The result shows that the proposed model is more efficient and dynamic and provided users with multidimensional evaluation based on open and distributed resources system.     

基于质量功能展开的产品配置模型

为使产品配置过程更符合用户的习惯,将质量功能展开引入配置过程,建立了基于质量功能展开的产品配置数学模型,其目标是根据用户的个性化需求,从可行配置方案中找到最符合用户需求的方案．为便于求解,将数学模型转换成等效的线性规划模型．实例仿真结果表明该模型是有效可行的．     

Improving quality function deployment analysis with the cloud MULTIMOORA method

Quality function deployment (QFD) is a quality guarantee method extensively used in various industries, which can help enterprises shorten the product design period and enhance the manufacturing and managing work. The task of selecting important engineering characteristics (ECs) in QFD is crucial and often involves multiple customer requirements (CRs). In this paper, a modified multi‐objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method based on cloud model theory (called C‐MULTIMOORA) is developed to determine the ranking order of ECs in QFD. First, the linguistic assessments provided by decision makers are transformed into normal clouds and aggregated by the cloud weighted averaging operator. Then, the weights of CRs are determined based on a maximizing deviation method with incomplete weight information. Finally, the importance of ECs is obtained using the C‐MULTIMOORA method. An empirical case conducted in an electric vehicle manufacturing organization is provided together with a comparative analysis to validate the advantages of our proposed QFD model.     

A fuzzy AHP approach to the determination of importance weights of customer requirements in quality function deployment

Quality function deployment (QFD) is an important tool in product planning that could contribute to increase in customer satisfaction and shorten product design and development time. During the QFD process, determination of the importance weights of customer requirements is a crucial and essential step. The analytic hierarchy process (AHP) has been used in weighting the importance. However, due to the vagueness and uncertainty existing in the importance attributed to judgement of customer requirements, the crisp pairwise comparison in the conventional AHP seems to be insufficient and imprecise to capture the degree of importance of customer requirements. In this paper, fuzzy number is introduced in the pairwise comparison of AHP. An AHP based on fuzzy scales is proposed to determine the importance weights of customer requirements. The new approach can improve the imprecise ranking of customer requirements which is based on the conventional AHP. Finally, an example of bicycle splashguard design is used to illustrate the proposed approach.     

Determining optimal levels of engineering characteristics in quality function deployment under multi-segment market

Customers often have various requirements and preferences on a product. A product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. In this paper, a methodology which mainly involves a market survey, fuzzy clustering, quality function deployment (QFD) and fuzzy optimization, is proposed to achieve the optimal target settings of engineering characteristics (ECs) of a new product under a multi-segment market. An integrated optimization model for partitioned market segments based on QFD technology is established to maximize the overall customer satisfaction (OCS) for the market considering the weights of importance of different segments. The weights of importance of market segments and development costs in the model are expressed as triangular fuzzy numbers in order to describe the imprecision caused by human subjective judgement. The solving approach for the fuzzy optimization model is provided. Finally, a case study is provided for illustrating the proposed methodology.     

A fuzzy group quality function deployment model for e-CRM framework assessment in agile manufacturing

The rapid growth of the Internet and the expansion of electronic commerce applications in manufacturing have given rise to electronic customer relationship management (e-CRM) which enhances the overall customer satisfaction. However, when confronted by the range of e-CRM methods, manufacturing companies struggle to identify the one most appropriate to their needs. This paper presents a novel structured approach to evaluate and select the best agile e-CRM framework in a rapidly changing manufacturing environment. The e-CRM frameworks are evaluated with respect to their customer and financial oriented features to achieve manufacturing agility. Initially, the e-CRM frameworks are prioritized according to their financial oriented characteristics using a fuzzy group real options analysis (ROA) model. Next, the e-CRM frameworks are ranked according to their customer oriented characteristics using a hybrid fuzzy group permutation and a four-phase fuzzy quality function deployment (QFD) model with respect to three main perspectives of agile manufacturing (i.e., strategic, operational and functional agilities). Finally, the best agile e-CRM framework is selected using a technique for order preference by similarity to the ideal solution (TOPSIS) model. We also present a case study to demonstrate the applicability of the proposed approach and exhibit the efficacy of the procedures and algorithms.     

A new mixed integer linear programming model for product development using quality function deployment

Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product development, determining the fulfillment levels of design requirements (DRs) is crucial during QFD optimization. However, in real world applications, the values of DRs are often discrete instead of continuous. To the best of our knowledge, there is no mixed integer linear programming (MILP) model in which the discrete DRs values are considered. Therefore, in this paper, a new QFD optimization approach combining MILP model and Kano model is suggested to acquire the optimized solution from a limited number of alternative DRs, the values of which can be discrete. The proposed model can be used not only to optimize the product development but also in other applications of QFD such as quality management, planning, design, engineering and decision-making, on the condition that DR values are discrete. Additionally, the problem of lack of solutions in integer and linear programming in the QFD optimization is overcome. Finally, the model is illustrated through an example.