In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuratio...In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuration method based on constraints and fuzzy decision for product family. The configuration method is evolved from constraint based product configuration. It employs fuzzy optimum selection in the reasoning process, which can select similar components when customers’ requirements can not be met precisely. In the configurator, product family is represented with GBOM(Generic Bill Of Material) and ACL(Article Characteristic List). Every node of GBOM has an ACL to list all instances of a component family. Constraints are attached to every node, which involves variable definition and constraints definition. In the reasoning process, constraint satisfaction and fuzzy optimum selection interact to search optimum solution. A prototype is developted to demonstrate how to run the configurator. The paper ends with a discussion of advantages, future work of the configuration method.展开更多
The paper studies on case-based reasoning of uncertain product attributes in configuration design of a product family. Interval numbers characterize uncertain product attributes. By interpolating a number of certain v...The paper studies on case-based reasoning of uncertain product attributes in configuration design of a product family. Interval numbers characterize uncertain product attributes. By interpolating a number of certain values randomly to replace interval numbers and making projection pursuit analysis on source cases and target cases of expanded numbers, we can get a projection value in the optimal projection direction. Based on projection value, we can construct a case retrieval model of projection pursuit that can handle coexisting certain and uncertain product attributes. The application examples of chainsaw configuration design show that case retrieval is highly sensitive to reliable results.展开更多
文摘In implementing mass customization, how to respond rapidly to customers’ requirements is a key problem. Configuration design is considered effective in early stage of product design. This paper studies a configuration method based on constraints and fuzzy decision for product family. The configuration method is evolved from constraint based product configuration. It employs fuzzy optimum selection in the reasoning process, which can select similar components when customers’ requirements can not be met precisely. In the configurator, product family is represented with GBOM(Generic Bill Of Material) and ACL(Article Characteristic List). Every node of GBOM has an ACL to list all instances of a component family. Constraints are attached to every node, which involves variable definition and constraints definition. In the reasoning process, constraint satisfaction and fuzzy optimum selection interact to search optimum solution. A prototype is developted to demonstrate how to run the configurator. The paper ends with a discussion of advantages, future work of the configuration method.
文摘The paper studies on case-based reasoning of uncertain product attributes in configuration design of a product family. Interval numbers characterize uncertain product attributes. By interpolating a number of certain values randomly to replace interval numbers and making projection pursuit analysis on source cases and target cases of expanded numbers, we can get a projection value in the optimal projection direction. Based on projection value, we can construct a case retrieval model of projection pursuit that can handle coexisting certain and uncertain product attributes. The application examples of chainsaw configuration design show that case retrieval is highly sensitive to reliable results.
