By introducing sequential and logical relationship factors into ASI (American SuppliersInstitute) Clausing/Makabe-QFD Model, a more practical model of QFD (Quality FunctionDeployment) is presented. Based on that the q...By introducing sequential and logical relationship factors into ASI (American SuppliersInstitute) Clausing/Makabe-QFD Model, a more practical model of QFD (Quality FunctionDeployment) is presented. Based on that the quality requirements are converted into designspecifications and technical measures step by step in this model, logical relationship factors canclassify the related Hows (how to do, the quality measures) into groups, each of which should belogical to individual What (what to do, the quality goal). Sequential factors can express theimplementing sequence of Hows. A feasibility evaluation method is proposed to eliminate the inferiorgroups of Hows. This improved QFD model can provide enough information to produce a practicalquality plan.展开更多
In the implementation of quality function deployment （QFD）, the determination of the target values of engineering characteristics is a complex decision process with multiple variables and multiple objectives that sh...In the implementation of quality function deployment （QFD）, the determination of the target values of engineering characteristics is a complex decision process with multiple variables and multiple objectives that should trade off, and optimize all kinds of conflicts and constraints. A fuzzy linear programming model （FLP） is proposed. On the basis of the inherent fuzziness of QFD system, triangular fuzzy numbers are used to represent all the relationships and correlations, and then, the functional relationships between the customer needs and engineering characteristics and the functional correlations among the engineering characteristics are determined with the information in the house of quality （HoQ） fully used. The fuzzy linear programming （FLP） model aims to find the optimal target values of the engineering characteristics to maximize the customer satisfaction. Finally, the proposed method is illustrated by a numerical example.展开更多
This paper presents an operational framework of unstructured decision-making approach involving quality function deployment(QFD)in an uncertain linguistic context.Firstly,QFD is extended to the multi-enterprise paradi...This paper presents an operational framework of unstructured decision-making approach involving quality function deployment(QFD)in an uncertain linguistic context.Firstly,QFD is extended to the multi-enterprise paradigm in a real-world manufacturing environment.Secondly,hesitant fuzzy linguistic term sets(HFLTSs),which facilitate the management and handling of information equivocality,are designed to construct a house of quality(HoQ)in the product planning process.The technique of computing with words is applied to bridge the gap between mechanisms of the human brain and machine processes with fuzzy linguistic term sets.Thirdly,a multi-enterprise QFD pattern is formulated as an unstructured decision-making problem for alternative infrastructure project selection in a manufacturing organization.The inter-relationships of cooperative partners are directly matched with a back propagation neural network(BPNN)to construct the multi-enterprise manufacturing network.The resilience of the manufacturing organization is considered by formulating an outranking method on the basis of HFLTSs to decide on infrastructure project alternatives.Finally,a real-world example,namely,the prototype manufacturing of an automatic transmission for a vehicle,is provided to illustrate the effectiveness of the proposed decision-making approach.展开更多
Quality function deployment （QFD） is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements （CRs） is really a very es- sential starting point in the impleme...Quality function deployment （QFD） is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements （CRs） is really a very es- sential starting point in the implementation of QFD, since it largely affects the target setting value of design requirements. This pa- per aims to propose a novel method to deal with the relative importance ratings （RIRs） of CRs problem considering customers＇ diversified requirements and unknown information on customers＇ weights, which is an indispensable process for determining the final importance ratings of CRs. First, a new concept of customer＇s assessment structure is proposed according to the basic idea of grey relational analysis （GRA）, and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers＇ personalized and diversified requirements. Furthermore, an im- mune particle swarm optimization （IPSO） algorithm is designed to solve the model, and the weight vector of customers is obtained. Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method＇s potential application in deter- mining the RIRs of CRs.展开更多
To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers ...To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.展开更多
Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration.Literatures on mass customization have been focused on mechani...Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration.Literatures on mass customization have been focused on mechanism of MC,but little on cus- tomer order decoupling point selection.The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization.Based on the analysis of other researchers’ achievements combining the demand problems of customer and enterprise,a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system.Considering relatively the decision mak- ers of independent functional departments as independent decision agents,a decision agent set is added as the third dimensionality to house of quality,the cubic quality function deployment is formed.The decision-making can be consisted of two procedures:the first one is to build each plane house of quality in various functional departments to express each opinions;the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment.Thus,department decision-making can well use its domain knowledge by ontology,and total decision-making can keep simple by avoiding too many customer requirements.展开更多
文摘By introducing sequential and logical relationship factors into ASI (American SuppliersInstitute) Clausing/Makabe-QFD Model, a more practical model of QFD (Quality FunctionDeployment) is presented. Based on that the quality requirements are converted into designspecifications and technical measures step by step in this model, logical relationship factors canclassify the related Hows (how to do, the quality measures) into groups, each of which should belogical to individual What (what to do, the quality goal). Sequential factors can express theimplementing sequence of Hows. A feasibility evaluation method is proposed to eliminate the inferiorgroups of Hows. This improved QFD model can provide enough information to produce a practicalquality plan.
基金supported by the National Natural Science Foundation of China (70571041).
文摘In the implementation of quality function deployment （QFD）, the determination of the target values of engineering characteristics is a complex decision process with multiple variables and multiple objectives that should trade off, and optimize all kinds of conflicts and constraints. A fuzzy linear programming model （FLP） is proposed. On the basis of the inherent fuzziness of QFD system, triangular fuzzy numbers are used to represent all the relationships and correlations, and then, the functional relationships between the customer needs and engineering characteristics and the functional correlations among the engineering characteristics are determined with the information in the house of quality （HoQ） fully used. The fuzzy linear programming （FLP） model aims to find the optimal target values of the engineering characteristics to maximize the customer satisfaction. Finally, the proposed method is illustrated by a numerical example.
基金supported by the National Key Research and Development Program of China(2016YFD0700605)the National Natural Science Foundation of China(51875151)Hefei Municipal Natural Science Foundation(2021029)。
文摘This paper presents an operational framework of unstructured decision-making approach involving quality function deployment(QFD)in an uncertain linguistic context.Firstly,QFD is extended to the multi-enterprise paradigm in a real-world manufacturing environment.Secondly,hesitant fuzzy linguistic term sets(HFLTSs),which facilitate the management and handling of information equivocality,are designed to construct a house of quality(HoQ)in the product planning process.The technique of computing with words is applied to bridge the gap between mechanisms of the human brain and machine processes with fuzzy linguistic term sets.Thirdly,a multi-enterprise QFD pattern is formulated as an unstructured decision-making problem for alternative infrastructure project selection in a manufacturing organization.The inter-relationships of cooperative partners are directly matched with a back propagation neural network(BPNN)to construct the multi-enterprise manufacturing network.The resilience of the manufacturing organization is considered by formulating an outranking method on the basis of HFLTSs to decide on infrastructure project alternatives.Finally,a real-world example,namely,the prototype manufacturing of an automatic transmission for a vehicle,is provided to illustrate the effectiveness of the proposed decision-making approach.
基金supported by the Fundamental Research Funds for the Central Universities(K5051399035BDY251412+1 种基金JB150601)the Soft Science Project of Shaanxi Province(2013KRZ25)
文摘Quality function deployment （QFD） is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements （CRs） is really a very es- sential starting point in the implementation of QFD, since it largely affects the target setting value of design requirements. This pa- per aims to propose a novel method to deal with the relative importance ratings （RIRs） of CRs problem considering customers＇ diversified requirements and unknown information on customers＇ weights, which is an indispensable process for determining the final importance ratings of CRs. First, a new concept of customer＇s assessment structure is proposed according to the basic idea of grey relational analysis （GRA）, and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers＇ personalized and diversified requirements. Furthermore, an im- mune particle swarm optimization （IPSO） algorithm is designed to solve the model, and the weight vector of customers is obtained. Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method＇s potential application in deter- mining the RIRs of CRs.
文摘To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.
基金Supported by the National Natural Science Foundation,China(No.70571019)the National High-Tech.R&D Program for CIMS,China(No.2002AA413110)the National Defense Basic Science and Research Foundation,China(No.A2320060097)
文摘Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration.Literatures on mass customization have been focused on mechanism of MC,but little on cus- tomer order decoupling point selection.The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization.Based on the analysis of other researchers’ achievements combining the demand problems of customer and enterprise,a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system.Considering relatively the decision mak- ers of independent functional departments as independent decision agents,a decision agent set is added as the third dimensionality to house of quality,the cubic quality function deployment is formed.The decision-making can be consisted of two procedures:the first one is to build each plane house of quality in various functional departments to express each opinions;the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment.Thus,department decision-making can well use its domain knowledge by ontology,and total decision-making can keep simple by avoiding too many customer requirements.
