scholarly journals Integrating a Voice of Customer to Create the Customer Needs Quality Function Deployment (CN-QFD) for a Sustainable New Product Development

Author(s):  
Thanyatorn Fongsatitkul ◽  
Yasutaka Kainuma
Author(s):  
Amir Mirzadeh Phirouzabadi

Nowadays,improving the quality of products, reducing cost and meeting customer’srequirements are necessary to shorten the time of new product development(NPD). NPD is used to describe the complete process of bringing a new product to market and conceptual design process(CDP) is at its early stage and has mostly changed from passive respond toaggressive one. Thus, this study proposed a practical method for CDP in NPDthrough three phases as Converting customers’ requirements to product specifications,Generating and selecting of concepts and Testing and finalizing the concepts byusing some different management-engineering techniques. Firstly, this papertried to prioritize customer’s requirements related to product by AHP (AnalyticHierarchy Process) and convert them to engineering parameters of TRIZ (Theoryof Inventive Problem Solving) in order to define the inventive principals.Next, based on QFD (Quality Function Deployment), we measured the weight valuesof inventive principals. Finally, as FMEA (Failure Mode and Effect Analysis)can analyze the weight values and reduce the sequential risk, then finalconceptual design was generated. At the end, a medical glasses was used as acase study of innovative design to validate the method and explain how thestrategies of this research for CDP.


2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Yu-Jie Zhao ◽  
Xin-xing Luo ◽  
Li Deng

In the fierce market environment, the enterprise which wants to meet customer needs and boost its market profit and share must focus on the new product development. To overcome the limitations of previous research, Chan et al. proposed a dynamic decision support system to predict the customer lifetime value (CLV) for new product development. However, to better meet the customer needs, there are still some deficiencies in their model, so this study proposes a CBR-based and MAHP-based customer value prediction model for a new product (C&M-CVPM). CBR (case based reasoning) can reduce experts’ workload and evaluation time, while MAHP (multiplicative analytic hierarchy process) can use actual but average influencing factor’s effectiveness in stimulation, and at same time C&M-CVPM uses dynamic customers’ transition probability which is more close to reality. This study not only introduces the realization of CBR and MAHP, but also elaborates C&M-CVPM’s three main modules. The application of the proposed model is illustrated and confirmed to be sensible and convincing through a stimulation experiment.


2015 ◽  
Vol 761 ◽  
pp. 594-598
Author(s):  
Syaiful Rizal Hamid ◽  
Boon Cheong Chew ◽  
Muhammad Azfar Abdullah ◽  
Sarah Halim

This paper discusses the development of E-saving glass (ESG) in Malaysia by using quality function deployment (QFD) method for market transformation. This paper focuses on two objectives, i.e., (i) to investigate the suitability of the ESG in Malaysian market for customer satisfaction, product quality and manufacturer competitiveness by using systematic tools of QFD process, and (ii) the implementation of ESG by looking at factors analysis based on QFD method and Malaysian market transformation. The QFD method is utilised by a multidisciplinary team to translate a set of customer requirements (the “voice of customer” (VOC)), market research and technical benchmarking data into an appropriate number of prioritised engineering targets that could be met by a new product design.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ming Li ◽  
Jie Zhang

Online reviews are crucial to any online business that wants to increase sales on the Internet. Customer reviews have information about product attributes, customer requirements (CRs), and shopping experience; mining reviews provide the direction of decision-making for new product development and design (NPDD). Besides, the information of customer preference has vagueness and uncertainty, and the accuracy of decision-making information directly affects the success of NPDD. This paper proposed a methodology that integrates the Kano model (KM), analytic hierarchy process (AHP), and quality function deployment (QFD) methods with intuitionistic fuzzy set (IFS) to solve decision-making problems in NPDD. By the new method, the web crawler technology was first applied to e-commerce web sites to collect raw data, and the representative CRs were extracted through combining LDA model with Apriori algorithm. Second, the intuitionistic fuzzy Kano model (IFKM) is proposed to evaluate adjustment coefficient of CRs and Kano categories via customer preference membership functions. Thirdly, overall weights which contained emotional needs (ENs) and functional needs (FNs) are obtained via intuitionistic fuzzy analytic hierarchy process (IFAHP); thus, the adjusted weights are calculated from IFKM and IFAHP. Next, the intuitionistic fuzzy quality function deployment (IFQFD) is proposed to acquire engineering characteristics (ECs) of weights through combining competition benchmarks and based on technical benchmarks to make goals for a company’s NPDD. Finally, the method was applied to study vertical-configured air conditioner (VAC) as an example. The results showed that the application of text mining and IFS to improve CS is both reliable and scientific.


Author(s):  
Thomas Y. Lee

The first step in product design and development involves concept generation. Concept generation involves identifying customer needs and then mapping those needs onto a set of product attributes (specifications). Traditional methods for concept generation involve focus groups, surveys, and anthropological studies to assess user needs. Techniques, like Quality Function Deployment (QFD), then guide designers in relating needs to explicit product specifications. In this paper, we propose to augment traditional methods for concept generation by automatically processing user generated online product reviews. We apply adaptive text extraction methods to automatically learn user needs and product attributes. Association rule mining is used to learn the mapping between needs and attributes. We summarize results from prior work for independently learning user needs and attribute specifications from product reviews and then discuss the application of these methods to concept generation for new product development.


Author(s):  
Chien-Wen Hung

In the process of new product development, the customer's feeling is usually fuzzy phenomenon, how to evaluate various factors is to test the developer's intelligence, this study takes the new product development process as the research object, and applies the Quality Function expansion (QFD) method to establish a decision support system with fuzzy processing ability. In this study, the first development of quality function expansion (QFD) applied to Customer voice collection and analysis and conversion to product specifications. Then, the integration of fuzzy theory and the provision of different commodity development solutions as the best choice for products.


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