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Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs.

Soonjo Kwon^1,2, Laetitia V Monnier^1,3, Raphael Barbau^1,4

¹Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.

Advanced Engineering Informatics

|May 22, 2026

Summary

This summary is machine-generated.

This study integrates design (STEP) and inspection (QIF) data using ontology and knowledge graphs to create a unified digital thread for smart manufacturing. This fusion enhances product quality assurance through improved data traceability and decision-making.

Keywords:

Data fusion Digital thread Industrial data standard Knowledge graph Ontology Product lifecycle

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Area of Science:

Manufacturing Engineering
Data Science
Ontology Engineering

Background:

The digital thread is crucial for smart manufacturing, requiring linked data across the product lifecycle.
Current methods struggle to unify design and inspection data, hindering automated quality assurance.
Ontology models and knowledge graphs have shown success in integrating engineering data.

Purpose of the Study:

To develop a standards-based digital thread by fusing as-designed (STEP) and as-inspected (QIF) data.
To address the lack of unified information models for automated product quality assurance.
To leverage ontology and knowledge graphs for integrating heterogeneous lifecycle data.

Main Methods:

Developed an automated pipeline for generating knowledge graphs from STEP and QIF data.
Implemented a mapping strategy to integrate separate STEP and QIF knowledge graphs.
Utilized rules and queries to demonstrate the integrated data's potential for decision-making.

Main Results:

Successfully generated knowledge graphs representing both STEP and QIF data.
Established a method for mapping and fusing these knowledge graphs into a cohesive digital thread.
Demonstrated the potential for enhanced product quality assurance through integrated data analysis.

Conclusions:

The proposed approach effectively fuses STEP and QIF data within a knowledge graph-based digital thread.
This integration provides a foundation for more automated and informed product quality assurance in smart manufacturing.
The use of ontology and knowledge graphs facilitates data associativity and traceability throughout the product lifecycle.