Integrating a novel intuitive fuzzy method with quality function deployment for product design: Case study on touch panels

In order to develop usable products, human needs and requirements have to be taken into consideration. By employing the QFD (Quality Function Deployment) method the human needs are systematically matched with the product characteristics, which can help to improve the product quality. In this paper the use of QFD in the area of usable products is discussed and a case study is presented to improve the supply chain of mazandaran spinning industry. The QFD method was used in the case study to translate the needs of usable yarn in spinning the carpet in the moist climate into product characteristics. The QFD analysis of the usable carpet revealed that the characteristics of the yarn were receiving the highest overall quality, which means that improving the design of the best quality yarn Proportional of the moist climate for spinning the carpet would lead to higher customer satisfaction. The importance of developing products that meet the customer or human needs is a priority area in the product development process. With knowledge in Selection of raw materials according to weather conditions it is possible to reveal information of the human needs and requirements. However, in the product development process it also is important to match the climate needs with the product characteristics, which can be achieved by using the QFD method. The knowledge of Selection of raw materials according to weather conditions and the use of the QFD method are therefore useful tools in designing high quality products.

Models and scientific evidence suggest that firms are more successful at new-product development if there is greater communication among marketing, engineering, and manufacturing. This paper examines communication patterns for two matched product-development teams where the key difference between the groups is that one used a phase-review development process and the other used Quality Function Deployment (QFD), a product-development process adopted recently at over 100 United States and Japanese firms. To our knowledge, this is the first head-to-head comparison of traditional U.S. product development processes with QFD. Our data suggest that QFD enhances communication levels within the core team (marketing, engineering, manufacturing). QFD changes communication patterns from “up-over-down” flows through management to more horizontal routes where core team members communicate directly with one another. On the other hand, the QFD team communicates less on planning information and less with members of the firm external to the team. If this paucity of external communication means that the team has the information it needs for product development, and the QFD process has provided an effective means for moving the information through the team, it is a positive impact of QFD. If the result means that QFD induces team insularity, even when the team needs to reach out to external information sources, it is a cause for concern.

Quality function deployment (QFD) has become a widely used tool in the product development process. It helps design teams gather the wants and needs of the customer and organize and utilize these data so that a product that satisfies the customer will be developed. One of the reasons for the success and acceptance of QFD is that it is a very versatile tool. The traditional matrices and process can be modified in many different ways to fit the needs of the product team. Like any innovation, however, QFD in practice has been implemented with varying degrees of success. This paper examines two QFD projects, one commercial and one defense, in order to identify the factors that favor successful implementation. It is posited that successful QFD requires both implementation effectiveness as well as the strategic accuracy of adoption—Firms need to adopt QFD for the right reasons, and effectively implement it once the choice has been made.

Designing the most efficient roadway illumination is a strategic and complex activity, as it requires consideration of both environmental and economic factors. The aim of this study is to propose a novel structured multi-methodological framework based on the systematic application of data envelopment analysis (DEA), qualityfunction deployment (QFD), and simple additive weighting (SAW) methods to support a critical decision-making process on roadway illumination design. First, the DEA is exercised to find efficient alternatives for roadway illumination. Then customer requirements are included and satisfied by the QFD. Lastly, using the DEA method, the SAW is used to rank the alternatives which are found to be efficient. As a case study, illumination alternatives for a typical urban roadway are analysed to select the most suitable choice in terms of energy and cost effectiveness, which are of course high priorities. The results show that the proposed multi-methodological approach takes advantages of DEA, QFD, and SAW to select an efficient roadway illumination alternative. The proposed approach also supplies a simple and very well-suited decision-making tool for this type of strategic decision-making issue.

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.

QFD (Quality Function Deployment) has been used to reflect the needs of customers in products, while TRIZ (a Russian acronym for Theory of Inventive Problem Solving) was developed to assist engineers in finding innovative solutions to technical problems in product development processes. However, no method has been proposed to integrate QFD with TRIZ effectively. This report describes a new method, named the Innovative Product Development Process (IPDP), which systematically integrates QFD with TRIZ and enables the effective and systematic creation of technical innovation for new products. In IPDP, the target products' functions and mechanisms are deployed in parallel into hierarchical structures, and the mechanism that most requires technical innovation is specified from an analysis of customers' needs by calculating a mechanism weight. Then, the technical problems to be solved are defined by considering the relationship between the specified mechanism and corresponding functions or quality characteristics, and technical innovation is executed by applying TRIZ. The effectiveness of IPDP was confirmed by applying it to the technical innovation of a washing machine.

Quality function deployment (QFD), a key tool to convert the customer needs into product features, is generally integrated into the New Product Development (NPD) process at the design stage. Prioritizing customer needs in a QFD process leads to using the resources (time, money, and staffing) effectively by eliminating the unimportant customer needs. The overall goal of the research was to develop a textile-based optical fiber sensor for automotive seat occupancy. The findings of this paper were focused on the design of experiments in our previous publication. In this paper, a research study was conducted to better understand market demands in terms of sensor performance characteristics for automotive seat weight sensors, as a part of the QFD House of Quality (HOQ) analysis. A survey was sent to more than 20 companies operating in the field of automotive seat weight sensors, and Original Equipment Manufacturers (OEM) via e-mail. Only five companies participated in this study due to competitive concerns and confidentiality reasons. However, the companies responded to the survey were of quality relevant to the research and could be perceived as representative of the group of experts. All 5 companies participated in the survey agreed on the first 5 most important sensor characteristics: reproducibility, accuracy, selectivity, aging, and resolution, where The Analytic Hierarchy Process (AHP) was applied to prioritize the sensor characteristics.

Capturing and prioritizing students’ requirements for course design by embedding Fuzzy-AHP and linear programming in QFD

Quality Function Deployment (QFD) has long been used as a successful design methodology in the heavy industrial and automotive industries. QFD helps designers utilize the ‘voice of the customer’, or customer requirements, to determine which engineering metrics or product specifications are the most essential [1]. This prioritization helps designers know what part of the product or process is most beneficial to focus on during design, resulting in products that better meet customer requirements and generate increased commercial success. QFD and most other design methodologies have rarely been applied to MEMS products [2]. In the case of QFD, the structure of the most common format of the tool dictates that engineering metrics should be related to parts characteristics in the second step of applying QFD. This causes difficulties in using the tool for MEMS as most MEMS do not have physical ‘parts’ that are assembled into a final device. Rather, MEMS have product specifications and a manufacturing process used to create the product. Generally there is a tight link between product and process in MEMS. This link has been utilized in creating a modified version of QFD that relates engineering metrics to design concepts, including product conceptualization and manufacturing process. The modified QFD utilizes aspects of Pugh Concept Selection, and differs from typical QFD primarily in consideration of product idea and manufacturing process in the early phases of product definition. The modified QFD was applied to a MEMS project whose goal was to develop a handheld device that allows users to control the selection and release of a variety of stored scents. The technique was also applied to a microscale heat exchanger for integrated circuits. The scent dispenser and heat exchanger were designed and prototyped at Stanford University in 2005 and 2006, respectively. The modified version of QFD gave insight early in the product definition phase on which design concept to pursue to prototype. Use of this and other design methodologies in the MEMS field could shorten the time it takes to progress through product development to volume manufacturing, and increase confidence in the marketability of the chosen design and manufacturing process. A case study demonstrating the effects of using modified QFD Phase II to assist in finding a good fit between technical capabilities and market application was performed by the author on an acoustic sensor technology [3].

Success in the market place is very much dependent on the ability to translate satisfaction into product properties and to do it as early as possible in the product development process. This paper addresses this translation process and problems of linking customer satisfaction to the early stages of product development. In the paper Quality Function Deployment (QFD) and a framework for linking internal quality and customer satisfaction are used as a theoretical basis for a case study from Volvo Car Corporation. The case study illustrates how QFD is used as a tool in the translation process and how Volvo by linking satisfaction to design in the improvement of the transmission system of the Volvo 850 achieved outstanding results.

Application of quality function deployment in the semiconductor industry: A case study

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.

In the study, based on the evaluation grid method (EGM) and fuzzy quality function deployment (QFD), taking the design of cultural and creative products as an example, we explored the importance of customer requirements and design elements and the correlation among various design elements. In this study, the combination of EGM and fuzzy QFD could avoid their respective defects. Firstly, we used the EGM to collect and analyse customer requirements and design elements. Secondly, we calculated the weight values of the customer requirements with the analytic hierarchy process (AHP). Thirdly, we established the fuzzy relation matrix between customer requirements and design elements. In addition, the importance of design elements was calculated based on the fuzzy theory. At the end, the result of this study has drawn a conclusion including the significance ordering of the design elements within the design dimension and the correlation between each design elements. Clear quantification of design elements has a guiding role in the design process, and the research methods of combining EGM with fuzzy QFD can solve many problems in the research process. Hope that the research and results can be used for reference in the future design work.

This chapter presents some results from a number of investigations concerning impact on concurrency and efficiency from the use of Design for X (DFX) tools in product development in Swedish industry. The project has been performed through an inter-disciplinary research programme with cooperation between Department of Machine Design at Royal Institute of Technology and Department of Psychology at Stockholm University. The studies were carried out in industrial sectors of mechanical and electro-mechanical products. Studied tools include DFA — Design for Assembly, FMEA — Failure Mode and Effects Analysis, QFD — Quality Function Deployment and EPS — Environmental Priority Strategies. The results have proven valid for product development in general. Important results are: • No tool will create concurrent engineering unless the organization of work is adapted to a high degree of co-operation between functions, e.g. marketing, design and manufacturing, and competence domains. • Use of the tools and/or information technology in product development could give excellent support to concurrent engineering if the implementation is made with regards to co-operative work. • Design for competition demands a simultaneous focusing on both product development process and the persons in the process.

This paper provides a framework to implement quality function deployment (QFD) with knowledge management (KM) in the form of an integrated quality and knowledge management system (IQKS). This inter-organizational information system enables the sharing of information among customers, manufacturers and suppliers in the new product development process. It links up various strategically independent and autonomous business entities together in a common product platform (CPP). Up to now little has been published academically on sharing vital information involving the give-away of a firm’s bargaining position about customers, product specification and process requirement. The common product platform facilitates an innovative organization to persuade like-minds in coming together and opening up useful and relevant information to all parties interested in creating a new level of competitive advantage in assessing the dynamics of market realities. They share knowledge and learn to support new organizational capabilities to leverage information technology that incorporate market knowledge, design knowledge, process knowledge and production knowledge.