QI-Digital: openBIS Data Model for an Additive Manufacturing Use Case
Creators: name: Reech, Maximilian Alexander
Publisher: name: Zenodo
Year: 2024
Subjects: subject: Additive manufacturing
subject: Data Store
subject: openBIS
subject: Data model
subject: QI-Digital

description: qi-digital-am: Additive Manufacturing Data Model

The following data model was created as part of the Quality Infrastructure Digital Project (QI-Digital) at the Federal Institute for Materials Research and Testing (BAM). The data model is tailored to the Additive Manufacturing (AM) use case, in particulary to the Laser Powder Bed Fusion (PBF-LB/M) process. It is compatible with the BAM Data Store project and was designed for the OpenBIS software and data management framework.

Overview

The data model serves as a framework to integrate all relevant data sources used within the Additive Manufacturing (AM) use case. The core of the data model is the (meta)data associated with manufactured components, with a focus on the traceability. Ensuring the traceability is crucial for performing QI-relevant analysis and maintaining quality standards throughout the manufacturing process.

Data Sources

The data model consolidates various data sources or sub-areas critical to the AM processs, including:





Laser Powder Bed Fusion (PBF-LB/M) Machine Data from the laser-based additive manufacturing system itself.

In-Process Thermography Thermal imaging data captured during the manufacturing process.

3D scan Surface geometry scans of the manufactured component.

CT scan Computed tomography data for structure analysis of the manufactured component.



Structure and File Overview

1. Masterdata Definition

The entities (objects) within the data model are defined in alignment with OpenBIS specification. These are provided in an importable Microsoft Excel file for easy integration:





File: masterdata.xlsx.This file defines the metadata of entity types for use within OpenBIS.



2. Entity Relationships

The relationships between the entities (objects) within the model are defined in a JSON format that follows the Object Type definitions Extension of OpenBIS:





File: relations.json.This file contains the connections between the defined Objects according to the openBIS parent-child relationships.



3. Inventory Organization

The organization of the inventory is outlined in JSON format according to the openBIS data structure.

The Inventory follows this structure:





File: inventories.json.



SPACE:

    PROJECT:

        COLLECTION: DEFAULT_OBJECT_TYPE

4. Build Job Structure

An example of an AM-project called build job is provided in JSON format. This AM-project is represented as an openBIS-PROJECT according to the following scheme:





File: buildjob.json.



PROJECT:

    COLLECTION:

        OBJECT:

Key Features





Compatibility with BAM Data Store:The data model is designed to integrate seamlessly with the BAM Data Store, the central institutional infrastructure for research data management (RDM), ensuring compatibility and ease of data management.

Metadata traceability:A primary goal of the data model is to ensure the complete traceability of data on additive manufacturing components. This enables robust evaluations aligned with possible Quality Infrastructure (QI) processes.

Support for Multiple Data Sources:The model supports data from a range of sources (machines, thermography, 3D, and CT scans), offering comprenhensive view of the additive manufacturing process.



Usage:

Importing the Data Model into openBIS





Import the masterdata.xlsx file into your openBIS instance to define the necessary Entity Types and Controlled Vocabularies.

Use the relations.json file to establish relationships between Entities and allow traceability.

Organize the inventory in openBIS according to the structure defined in inventories.json.

For a specific AM-project, the exemplary structure outlined in buildjob.json can be followed to manage the data objects related to manufacturing tasks.



Conclusion:

This data model is designed as a flexible and comprenhensive solution for managing additive manufacturing data within the openBIS framework. For more information on integrating this model into your existing workflows or for additional documentation, please contact Dr.-Ing. Mehran Monavari (mehran.monavari@bam.de).

References





Bauch, A.; Adamczyk, I.; Buczek, P.; Elmer, F.-J.; Enimanev, K.; Glyzewski, P.; Kohler, M.; Pylak, T.; Quandt, A.; Ramakrishnan, C.; Beisel, C.; Malmström, L.; Aebersold, R.; Rinn, B. openBIS: A Flexible Framework for Managing and Analyzing Complex Data in Biology Research. BMC Bioinformatics 2011, 12 (1), 468.  https://doi.org/10.1186/1471-2105-12-468.

Barillari, C.; Ottoz, D. S. M.; Fuentes-Serna, J. M.; Ramakrishnan, C.; Rinn, B.; Rudolf, F. openBIS ELN-LIMS: An Open-Source Database for Academic Laboratories. Bioinformatics 2016, 32 (4), 638–640. https://doi.org/10.1093/bioinformatics/btv606.

R. El-Athman, J. Rädler, O. Löhmann, A. Ariza de Schellenberger, & T. Muth, The BAM Data Store: Piloting an openBIS-Based Research Data Infrastructure for Materials Science and Engineering, 1st Conference on Research Data Infrastructure (CoRDI), Karlsruhe, Germany, Sep. 2023, Zenodo. https://doi.org/10.5281/zenodo.8359945.