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Precision Measurements and Parametric Models of Vertebral Endplates

Precision Measurements and Parametric Models of Vertebral Endplates

Published on: September 17, 2019

Additive Manufacturing In-situ and Ex-Situ Geometric Data Registration.

Shaw C Feng¹, Yan Lu¹, Albert T Jones¹

¹Systems Integration Division, National Institute of Standards and Technology, 100 Bureau Drive, MS 8260, Gaithersburg, MD 20899.

Journal of Computing and Information Science in Engineering

|September 18, 2023

Summary

This summary is machine-generated.

Data alignment is crucial for integrating diverse measurement data from Laser-Based Powder Bed Fusion of Metals. This study presents a data registration procedure to spatially align datasets for advanced analytics and part qualification in Additive Manufacturing.

Keywords:

additive manufacturing data alignment data registration meta data modeling

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Last Updated: Jul 16, 2025

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Published on: September 17, 2019

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Area of Science:

Materials Science
Mechanical Engineering
Data Science

Background:

The proliferation of measurement devices in Laser-Based Powder Bed Fusion of Metals (L-PBF) generates diverse datasets.
These datasets originate from unique coordinate systems and formats, hindering integrated analysis.
Effective data alignment is essential for leveraging this information.

Purpose of the Study:

To introduce a standardized data registration procedure for L-PBF.
To demonstrate data alignment to a single reference coordinate system.
To facilitate downstream applications like data analytics, AI, and part qualification.

Main Methods:

Development of a data-registration procedure.
Spatial alignment of disparate datasets to a common reference coordinate system.
Illustrative example of the data alignment process.

Main Results:

Successful alignment of measurement data from various sources into a unified coordinate system.
Demonstration of a practical data-registration workflow.
Establishment of a prerequisite for advanced data analysis.

Conclusions:

Data alignment is a critical step for effective data utilization in Additive Manufacturing.
The presented procedure enables the integration of multi-source data for L-PBF.
Standardized data registration supports AI, data analytics, and part qualification in metal AM.