---
_id: '63543'
abstract:
- lang: eng
  text: "<jats:title>Abstract</jats:title>\r\n          <jats:p>Current megatrends
    are influencing industrial production and leading to ever shorter innovation cycles.
    The resulting fast pace of production requirements requires an accelerated development
    of production systems and an associated increase in efficiency in factory planning.
    Due to its knowledge-intensive activities, rough factory planning promises great
    potential to be supported in its activities by innovative technologies such as
    artificial intelligence. However, industrial companies face the challenge to recognize
    the potential of artificial intelligence (AI) in rough planning and to evaluate
    possible applications in their business context. As a result, a systematic approach
    for analyzing AI potential in rough factory planning was developed as part of
    this work. The system includes a procedural model and several artefacts used in
    it, which support the identification and evaluation of AI potential in organizations.
    This approach not only streamlines the planning process but also aligns with sustainable
    manufacturing principles by enhancing resource efficiency, promoting intelligent
    system design, and fostering innovation in product development and manufacturing
    processes.</jats:p>"
author:
- first_name: Dominik
  full_name: Kürpick, Dominik
  last_name: Kürpick
- first_name: Jan-Philipp
  full_name: Disselkamp, Jan-Philipp
  last_name: Disselkamp
- first_name: Jonas
  full_name: Lick, Jonas
  last_name: Lick
- first_name: Aschot
  full_name: Hovemann, Aschot
  last_name: Hovemann
- first_name: Roman
  full_name: Dumitrescu, Roman
  id: '16190'
  last_name: Dumitrescu
citation:
  ama: 'Kürpick D, Disselkamp J-P, Lick J, Hovemann A, Dumitrescu R. Systematic AI
    Potential Analysis for Sustainable Rough Factory Planning. In: <i>Lecture Notes
    in Mechanical Engineering</i>. Springer Nature Switzerland; 2025. doi:<a href="https://doi.org/10.1007/978-3-031-93891-7_84">10.1007/978-3-031-93891-7_84</a>'
  apa: Kürpick, D., Disselkamp, J.-P., Lick, J., Hovemann, A., &#38; Dumitrescu, R.
    (2025). Systematic AI Potential Analysis for Sustainable Rough Factory Planning.
    In <i>Lecture Notes in Mechanical Engineering</i>. Springer Nature Switzerland.
    <a href="https://doi.org/10.1007/978-3-031-93891-7_84">https://doi.org/10.1007/978-3-031-93891-7_84</a>
  bibtex: '@inbook{Kürpick_Disselkamp_Lick_Hovemann_Dumitrescu_2025, place={Cham},
    title={Systematic AI Potential Analysis for Sustainable Rough Factory Planning},
    DOI={<a href="https://doi.org/10.1007/978-3-031-93891-7_84">10.1007/978-3-031-93891-7_84</a>},
    booktitle={Lecture Notes in Mechanical Engineering}, publisher={Springer Nature
    Switzerland}, author={Kürpick, Dominik and Disselkamp, Jan-Philipp and Lick, Jonas
    and Hovemann, Aschot and Dumitrescu, Roman}, year={2025} }'
  chicago: 'Kürpick, Dominik, Jan-Philipp Disselkamp, Jonas Lick, Aschot Hovemann,
    and Roman Dumitrescu. “Systematic AI Potential Analysis for Sustainable Rough
    Factory Planning.” In <i>Lecture Notes in Mechanical Engineering</i>. Cham: Springer
    Nature Switzerland, 2025. <a href="https://doi.org/10.1007/978-3-031-93891-7_84">https://doi.org/10.1007/978-3-031-93891-7_84</a>.'
  ieee: 'D. Kürpick, J.-P. Disselkamp, J. Lick, A. Hovemann, and R. Dumitrescu, “Systematic
    AI Potential Analysis for Sustainable Rough Factory Planning,” in <i>Lecture Notes
    in Mechanical Engineering</i>, Cham: Springer Nature Switzerland, 2025.'
  mla: Kürpick, Dominik, et al. “Systematic AI Potential Analysis for Sustainable
    Rough Factory Planning.” <i>Lecture Notes in Mechanical Engineering</i>, Springer
    Nature Switzerland, 2025, doi:<a href="https://doi.org/10.1007/978-3-031-93891-7_84">10.1007/978-3-031-93891-7_84</a>.
  short: 'D. Kürpick, J.-P. Disselkamp, J. Lick, A. Hovemann, R. Dumitrescu, in: Lecture
    Notes in Mechanical Engineering, Springer Nature Switzerland, Cham, 2025.'
date_created: 2026-01-09T13:17:31Z
date_updated: 2026-01-09T13:18:45Z
department:
- _id: '563'
doi: 10.1007/978-3-031-93891-7_84
language:
- iso: eng
place: Cham
publication: Lecture Notes in Mechanical Engineering
publication_identifier:
  isbn:
  - '9783031938900'
  - '9783031938917'
  issn:
  - 2195-4356
  - 2195-4364
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Systematic AI Potential Analysis for Sustainable Rough Factory Planning
type: book_chapter
user_id: '15782'
year: '2025'
...