Data underlying the MSc Thesis: : Digital Platforms for Industrial Metaverse Applications: A Framework to Identify Data Quality Insufficiencies

DOI:10.4121/794cc257-f07b-4037-8b3a-4f42b51b1ee5.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/794cc257-f07b-4037-8b3a-4f42b51b1ee5

Datacite citation style

Biermann, Niklas (2023): Data underlying the MSc Thesis: : Digital Platforms for Industrial Metaverse Applications: A Framework to Identify Data Quality Insufficiencies. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/794cc257-f07b-4037-8b3a-4f42b51b1ee5.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Nvidia Omniverse Data Quality Gate

This project contains the source code to an Nvidia Omniverse extension capable of flawlessly identifying the six most critical data quality insufficiencies within the 3D environment of an automitve manufacturer's virtual factory models, perform an applicable analysis of the data obtained from this identification and derive concrete KPIs.


Project Description

Problem:

Data quality assessments of virtual factory models visualised in the Nvidia Omniverse 3D environment have to be conducted fully manually. This procedure is time-consuming and prone to errors, causing the benefits of the Nvidia Omniverse in the automotive manufacturing sector to be outweighed by the costs of ensuring sufficient data quality.


Objective:

This software extension to the Nvidia Omniverse is capable of automatically identifying the most critical insufficiencies within a virtual factory model and performing an analysis of the results to compute adequate KPIs. Based on these KPIs, minimum data quality requirements are to be defined that need to be met by virtual factory models coming from the Factory Assembler to be published for visualisation in the Nvidia Omniverse. Thereby, a data quality gate is created that ensures a certain quality standard of data in the Nvidia Omniverse.


Get Started:

1. In the Omniverse App open extension manager: Window → Extensions.

2. In the Extension Manager Window open a settings page, with a small gear button in the top left bar.

3. In the settings page there is a list of Extension Search Paths. Add file path to `exts` subfolder there as another search path

4. Now you can find omniverse.quality.gate extension in the top left search bar. Select and enable it.

5. "Nvidia Omniverse Data Quality Gate" window will pop up in bottom right corner. Extension Manager watches for any file changes and updates extension following a hotreload.


Functionalities:

`quality_checks.py`: Identification functions for each of the six data quality insufficiency checks (+ relevant reoccuring functions enbaling these checks)

`ui_window.py`: All UI specifications including window set-up and automatic data analysis to create KPI dashboard



History

  • 2023-06-20 first online, published, posted

Publisher

4TU.ResearchData

Format

Python (.py), Image (.png)

Organizations

TU Delft, Faculty of Technology, Policy and Management, Department of Management of Technology (MoT)

DATA

Files (4)