| Quality function deployment(QFD)is a structured product development or service design method that is market-oriented and driven by customer requirements(CRs).It can effectively identify CRs,which would be broken down through the house of quality(HOQ)and then integrated into all stages of the whole process of product development to ensure that the developed products could have better quality and meet the requirements of customers as much as possible.The whole process of QFD-based product development exhibits the important ideas of system engineering,which means a complex system with original information input,intermediate information processing,and result information output.It has been proved by many practices and applications that QFD theory has a significant role in strengthening team communication,shortening product development cycles,reducing product design changes,decreasing product production costs,and improving product quality.The construction and application of the product planning HOQ is the focus and key point of QFD research,and it is also the main research object of this research.There have been numerous researches on QFD theory and applications.However,the faced environment of product development is becoming more and more complicated and the uncertainty and fuzzy degree of related evaluation information are also increasing with the rapid development of social-economic system and heterogeneous CRs.As a result,the applicability of the traditional QFD method has been greatly limited.Simultaneously,QFDbased product development is a typical group collaboration process,and traditional QFD research does not fully consider the heterogeneity of group members.Therefore,the traditional QFD theory based on exact numbers is inadequate in dealing with fuzzy information and fully considering the heterogeneity of group members.In view of the problem,this research carried out a systematic study on the QFD theory and application under the environment of group fuzzy information by combining fuzzy multi-attribute group decision-making theory with traditional QFD.The main contents and contributions of this research can be concluded as follows.1)A systematic CRs identification model based on the SECI model that belongs to knowledge management theory was established.Considering the method of collecting CRs is systematic-insufficient and lacks comprehensiveness in the traditional QFD,Gemba walk,critical incident technology,and text analysis of social media were introduced for comprehensively collecting the externalized and potential CRs as much as possible.Then,a CR deployment table was proposed to deploy the initial voice of customers(VOC)to externalized CR items.Finally,taking the relationships among those scattered CR items into consideration,affinity diagramming was introduced to group the items into representative CRs.The empirical case of collecting the requirements of passengers with respect to the second class seat of HSR in China was used to verify the applicability and efficiency of the proposed model.2)Two CRs’ importance analysis methods that respectively based on ordinal-scale information and intuitionistic fuzzy sets(IFS)under multiple-preference information forms were constructed.On the one hand,considering the situation in which customers have insufficient cognition of product requirements or their own knowledge accumulation is limited,the importance evaluation information on CRs and the importance of different customers are both expressed in the form of ordinal scale information.By integrating the customer’s individual preference vectors,defining the element extraction sequence,and constructing the comprehensive preference vector,the importance ranking method for CRs under fuzzy ordinal scale information was constructed.On the other hand,taking full account of the heterogeneity among customers,the importance evaluation information on CRs which would be unified IFS is expressed in different forms such as precise numbers,linguistic variables,and IFS according to the preference of each customer.Then,an analysis method for CRs’importance based on the uniformed IFS was established.In addition,considering the dynamic variability of customers’preferences companied with the time and environment,a sensitivity analysis of each CR was conducted to determine the change range of each CR so that to monitor and adjust the product development strategies in real-time.3)The theoretical research on PHFLTSs was improved and a CPT-based method for ranking engineering characteristics(ECs)under proportional hesitant fuzzy linguistic environment with a large-scale group was also constructed.First,considering the increasing complexity of product development and the problems of information loss and distortion in traditional fuzzy information processing methods,the proportional hesitant fuzzy linguistic term set(PHFLTS)that can simultaneously considers the linguistic variables and their corresponding proportional information was introduced as an information processing tool.Further,the theoretical research on PHFLTS was improved and the corresponding fuzzy multiple-attributes group decision-making methods were proposed.Second,in order to take more stakeholders into account in the process of product development,a ranking method of ECs under proportional hesitant fuzzy linguistic environment with a large-scale group was constructed based on the previous therotical research on PHFLTS.Particularly,a clustering method was proposed to determine the weight of each decision-maker in hesitant fuzzy linguistic settings.In addition,considering the different psychological of QFD experts when facing different risks and benefits,the cumulative prospect theory was introduced and a improved PHFL-CPT method was proposed to rank the priority of ECs for improving the accuracy and reliability of the results.4)A three-stage risk management framework based on fuzzy linguistic QFD and nonlinear goal programming was established for dealing with the risk management problem of hazardous material road transportation.The practical application is the purpose of theoretical research.In order to expand the application fields of QFD theory and verify the feasibility and effectiveness of the proposed methods,the risk management problem of hazardous material road transportation was conducted based on the previous theoretical research on PHFLTS.First,in an overall view,a risk management HOQ was constructed based on thestructure of product planning HOQ,and the relevant fuzzy evaluation information was collected.Then,a fuzzy-AHP method was introduced to evaluate the risk based on the identified risk factors.Next,the F-FMEA method was proposed for evaluating the potential failures of risk control measures and determining the risk adjustment coefficient with respect to each risk control measure.Finally,a nonlinear goal programming model was established to derive the optimized fulfillment level of each risk control measure with the goal of maximizing the total risk control efficiency.The obtained results also provided efficient decision-making supporting to risk management of hazardous material road transportation. |
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