---
_id: '67439'
abstract:
- lang: eng
  text: "Predictive maintenance is a key requirement for autonomous systems, particularly
    in the rail sector where it enables autonomous rail operation.\r\n\r\nIn order
    to perform effective condition monitoring and predictive maintenance the integration
    of operational data, engineering models, and hybrid predictive models is necessary
    and enables a centralised access to all necessary data. The digital twin (DT)
    concept fulfils this requirements and is technically realised in the Eclipse BaSyx
    Asset Administration Shell (AAS) environment as a central hub for capturing models,
    measuring data and maintenance information. The implementation makes use of Industrial
    Digital Twin Association-Standards (IDTA) and models the train components in a
    hierarchical structure.\r\n\r\nHowever, in the current BaSyx implementation manually
    creating the hierarchical DT structures is error-prone and difficult to standardize.
    This paper presents an adapter that creates and maintains hierarchical DT structures
    based on predefined concepts. The adapter facilitates the annotation of heterogeneous
    data and models, their mapping to a desired DT hierarchy, and their deployment
    into a standardized BaSyx-based AAS infrastructure by providing an easy-to-use
    user interface. The hierarchical DT structure resembles the hierarchical structure
    of the system and its models and allows the exchange of parts or components physically
    and virtually.\r\n\r\nThe development of the adapter accompanied the development
    of physical, data-driven and hybrid models to enable predictive maintenance for
    rubber-metal springs in rail bogies. The application is illustratively for predictive
    maintenance in the rail sector and yielded practical insights for engineering
    cyber-physical systems.\r\n\r\nBy addressing current user interface limitations,
    this work provides a scalable, standard-compliant approach for integrating different
    data sources, creating the initial DT structure and continuously operating a DT
    in rail maintenance management."
author:
- first_name: Andreas Maximilian
  full_name: Schultz, Andreas Maximilian
  id: '40599'
  last_name: Schultz
- first_name: Jill Mercedes
  full_name: Linneweber, Jill Mercedes
  id: '57639'
  last_name: Linneweber
  orcid: https://orcid.org/0009-0002-1910-358X
- first_name: Max
  full_name: Kelber, Max
  id: '70188'
  last_name: Kelber
- first_name: Janik
  full_name: Hark, Janik
  last_name: Hark
- first_name: Laura
  full_name: Müller, Laura
  id: '44605'
  last_name: Müller
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
- first_name: Iryna
  full_name: Mozgova, Iryna
  id: '95903'
  last_name: Mozgova
citation:
  ama: Schultz AM, Linneweber JM, Kelber M, et al. <i>Digitaler Zwilling für die Zustandsüberwachung
    und vorausschauende Instandhaltung im ATO</i>.; 2026.
  apa: Schultz, A. M., Linneweber, J. M., Kelber, M., Hark, J., Müller, L., Sextro,
    W., &#38; Mozgova, I. (2026). <i>Digitaler Zwilling für die Zustandsüberwachung
    und vorausschauende Instandhaltung im ATO</i>.
  bibtex: '@book{Schultz_Linneweber_Kelber_Hark_Müller_Sextro_Mozgova_2026, place={Lemgo},
    title={Digitaler Zwilling für die Zustandsüberwachung und vorausschauende Instandhaltung
    im ATO}, author={Schultz, Andreas Maximilian and Linneweber, Jill Mercedes and
    Kelber, Max and Hark, Janik and Müller, Laura and Sextro, Walter and Mozgova,
    Iryna}, year={2026} }'
  chicago: Schultz, Andreas Maximilian, Jill Mercedes Linneweber, Max Kelber, Janik
    Hark, Laura Müller, Walter Sextro, and Iryna Mozgova. <i>Digitaler Zwilling für
    die Zustandsüberwachung und vorausschauende Instandhaltung im ATO</i>. Lemgo,
    2026.
  ieee: A. M. Schultz <i>et al.</i>, <i>Digitaler Zwilling für die Zustandsüberwachung
    und vorausschauende Instandhaltung im ATO</i>. Lemgo, 2026.
  mla: Schultz, Andreas Maximilian, et al. <i>Digitaler Zwilling für die Zustandsüberwachung
    und vorausschauende Instandhaltung im ATO</i>. 2026.
  short: A.M. Schultz, J.M. Linneweber, M. Kelber, J. Hark, L. Müller, W. Sextro,
    I. Mozgova, Digitaler Zwilling für die Zustandsüberwachung und vorausschauende
    Instandhaltung im ATO, Lemgo, 2026.
date_created: 2026-10-08T14:03:01Z
date_updated: 2026-10-08T14:03:12Z
ddc:
- '006'
department:
- _id: '741'
file:
- access_level: closed
  content_type: application/pdf
  creator: schultza
  date_created: 2026-10-08T14:00:25Z
  date_updated: 2026-10-08T14:00:25Z
  file_id: '67441'
  file_name: Poster DMB Digitaler Zwilling.pdf
  file_size: 1422611
  relation: main_file
  success: 1
file_date_updated: 2026-10-08T14:00:25Z
has_accepted_license: '1'
language:
- iso: ger
place: Lemgo
project:
- _id: '1355'
  name: enableATO – Automatisierter Bahnverkehr als Backbone für eine nachhaltige,
    vernetzte Mobilität im ländlichen Raum
publication_status: published
status: public
title: Digitaler Zwilling für die Zustandsüberwachung und vorausschauende Instandhaltung
  im ATO
type: misc
user_id: '40599'
year: '2026'
...