In a circular economy (CE), materials, components and products should be kept at the highest level of functionality, while phenomena like dilution, mixing and contamination, often referred to as the loss of resources, should be avoided. One method that can assess the performance of systems to concentrate or avoid dilution of resources is Statistical Entropy Analysis (SEA). Up till now, the method has been applied on the substance level (elements and compounds) only, but showed its applicability to various scales and a variety of systems. Further development of the method allowed to consider information on the product, component and material levels, which makes the method applicable to different combinations of CE strategies, both destructive (e.g. recycling) and non-destructive (e.g. reuse). The method is demonstrated on a simplified vehicle life-cycle, which is modeled through four component groups and six materials. It shows that the method allows to evaluate different CE strategies and identify critical stages which lead to the most severe resource and functionality losses. Based on the method's results, it is possible to determine a perfect circularity reference level, representing a system state that preserves functionality and avoids resource losses. The introduction of a circularity reference level enables the establishment of a framework for resource effectiveness in which diluting and concentrating effects of activities (e.g. sorting) are quantified. The distance of a system to an ideal circular state determines the deviation from a resource-effective system that maintains the original product functionality over a maximum period of time, with minimal efforts.

在循环经济（CE）中，应将材料，组件和产品的功能保持在最高水平，同时应避免诸如稀释，混合和污染之类的现象（通常被称为资源损失）。可以评估系统性能以集中或避免资源浪费的一种方法是统计熵分析（SEA）。迄今为止，该方法仅在物质水平（元素和化合物）上应用，但显示出其在各种规模和各种系统上的适用性。该方法的进一步发展允许考虑有关产品，组件和材料级别的信息，这使得该方法适用于破坏性（例如循环利用）和非破坏性（例如再利用）CE策略的不同组合。该方法在简化的汽车生命周期中得到了证明，该生命周期通过四个组件组和六种材料进行建模。它表明该方法可以评估不同的CE策略并确定导致最严重的资源和功能损失的关键阶段。根据该方法的结果，可以确定一个完美的圆形度参考级别，该级别表示保留功能并避免资源损失的系统状态。引入循环参考水平可以建立资源有效性的框架，其中可以量化活动的稀释和集中效应（例如分类）。