The digital transformation of manufacturing requires digitalization, including automatic and efficient data exchange. Model-based definitions (MBDs) capture digital product definitions, in order to eliminate error-prone information exchange associated with traditional paper-based drawings and to provide contextual information through additional metadata. The flow of MBDs extends throughout the product lifecycle (including the design, analysis, manufacturing, in service life, and retirement stages) and can be extended beyond the typical geometry and tolerance information within a computer-aided design. In this paper, the MBDs are extended to include materials information, via dynamic linkages. To this end, a model-based feature information network (MFIN) is created to provide a comprehensive framework that facilitates storing, updating, searching, and retrieving of relevant information across a product’s lifecycle. The use case of a damage tolerant analysis for a compressor bladed-disk (blisk) is demonstrated, in Ti-6Al-4V blade(s) linear friction welded to the Ti-6Al-4V disk, creating well-defined regions exhibiting grain refinement and high residuals stresses. By capturing the location-specific microstructure and residual stress values at the weld regions, this information is accessed within the MFIN and used for downstream damage tolerant analysis. The introduction of the MFIN framework facilitates access to dynamically evolving data for use within physics-based models (resulting in the opportunity to reduce uncertainty in subsequent prognosis analyses), thereby enabling a digital twin description of the component or system.

制造业的数字化转型需要数字化，包括自动和高效的数据交换。基于模型的定义（MBD）捕获数字产品定义，以便消除与传统的基于纸张的图纸相关的易于出错的信息交换，并通过其他元数据提供上下文信息。MBD的流程扩展到整个产品生命周期（包括设计，分析，制造，使用寿命和报废阶段），并且可以扩展到计算机辅助设计中的典型几何形状和公差信息之外。在本文中，MBD通过动态链接扩展为包括材料信息。为此，创建了基于模型的特征信息网络（MFIN），以提供有助于存储，更新，搜索，以及在产品生命周期中检索相关信息。在将Ti-6Al-4V叶片线性摩擦焊接到Ti-6Al-4V磁盘上的过程中，证明了压缩机叶片盘（叶盘）的损伤容限分析的用例，创建了清晰的区域，细化了晶粒和高残留应力。通过捕获焊缝区域的特定位置的微结构和残余应力值，可以在MFIN中访问此信息，并将其用于下游的公差容限分析。MFIN框架的引入促进了动态演化数据的访问，以便在基于物理学的模型中使用（从而有机会减少后续预后分析中的不确定性），从而实现了组件或系统的数字孪生描述。