Abstract

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.

Highlights

  • The concept of the digital twin aims to create a digital representation of a serializable component or system, which can be used to predict its future performance based on the current available knowledge [1, 2]

  • This paper presents a framework for data exchange, archival, and retrieval, as well as dynamically updating pertinent information throughout the lifecycle of a component to realize the digital twin representation, which is demonstrated for prognosis of its service life

  • The primary focus of this paper is to describe the model-based feature information network (MFIN) framework and illustrate the implementation of the MFIN to enable storing and retrieval of material definitions and structural analysis information, with an emphasis on location-specific material data

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Summary

Introduction

The concept of the digital twin aims to create a digital representation of a serializable component or system, which can be used to predict its future performance based on the current available knowledge [1, 2]. The current work presents a dynamically linked approach and proposes a framework, namely the model-based feature information network (MFIN), to connect material definitions to locations within the component’s geometry.

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