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An Infinite Regress Model of Design Change Propagation in Complex Systems

机译:复杂系统中设计变更传播的无限回归模型

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In complex systems, design changes of one component or subsystem may require the redesign of other components or be stimulated by the redesign of other components. Changes propagate through the design dependency paths among the components of a system and thus present challenges to the design and management of the system. Therefore, an assessment of the influence and susceptibility of components is useful for system design decisions such as which components to standardize, modularize, or embed flexibility to address future design changes. Finding the overall influence or susceptibility of individual components throughout a complex system is an infinite regress problem, as both the sources and targets of the influences are the same set of components. A component influences some other components, which influence other components, and so on. Such influences can be propagated back to the initiating components through cycles of design dependencies among components. In this paper, we model change propagation in complex systems as an infinite regress problem and derive eigenvector-based indicators of component influence and susceptibility. We demonstrate our method based on several case studies.
机译:在复杂的系统中,一个组件或子系统的设计更改可能需要对其他组件进行重新设计,或者被其他组件的重新设计所激发。更改通过系统组件之间的设计依赖关系路径传播,因此对系统的设计和管理提出了挑战。因此,对组件的影响和敏感性的评估对于系统设计决策(例如哪些组件要标准化,模块化或嵌入灵活性以应对未来的设计变更)很有用。找到整个复杂系统中各个组件的总体影响或敏感性是一个无限回归的问题,因为影响的来源和目标都是同一组组件。一个组件会影响其他一些组件,这些组件会影响其他组件,依此类推。这些影响可以通过组件之间的设计依赖性循环传播回初始组件。在本文中,我们将复杂系统中的变化传播建模为无限回归问题,并得出基于特征向量的成分影响和敏感性指标。我们基于几个案例研究证明了我们的方法。

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