排序方式: 共有4条查询结果,搜索用时 0 毫秒
1
1.
IntroductionMarket competitiveness forces enterprises todeliver a variety of products while keeping massproduction efficiency[1]. This leads to the masscustomization, for which product family development is the effective means[2, 3]. Modularity andstandardization are promising tools in product family development[4]. Many authors view modularityas the key to improving the cost-variety trade-ofin product development[5, 6]. Products built aroundmodular architectures can be more easily variedwith… 相似文献
2.
3.
Design for life-time performance and proper maintenance measures are usually needed to prolong the mean-time-between-failures
of complex equipments such as internal combustion engines. To reach this, it is important to obtain the information of time-varying
system performance in design stage and to identify the structural change at each moment. So a multidisciplinary model based
method is studied in this paper to unify the time-varying performance(TVP) prediction and system identification(SI) of equipments.
The related multidisciplinary model in this paper should be not only precise to give simulation results but also sensitive
to the variation of system parameters. So the varying history of system performance along with the structural change can be
obtained from the model. Then the value of system parameters can be identified by seeking roots with given detected responding
data and relationship between system responding data and system parameters. A case study on a low power gasoline engine shows
that the method presented in this paper can provide useful information for the development and maintenance of complex equipments. 相似文献
4.
A Method of Clustering Components into Modules Based on Products' Functional and Structural Analysis
Modularity is the key to improving the cost-variety trade-off in product development. To achieve the functional independency and structural independency of modules, a method of clustering components to identify modules based on functional and structural analysis was presented. Two stages were included in the method. In the first stage the products' function was analyzed to determine the primary level of modules. Then the objective function for modules identifying was formulated to achieve functional independency of modules. Finally the genetic algorithm was used to solve the combinatorial optimization problem in modules identifying to form the primary modules of products. In the second stage the cohesion degree of modules and the coupling degree between modules were analyzed. Based on this structural analysis the modular scheme was refined according to the thinking of struc- tural independency. A case study on the gear reducer was conducted to illustrate the validity of the presented method. 相似文献
1