Bretones Cassoli, Beatriz ; Hoffmann, Felix ; Metternich, Joachim (2021)
Comparison of AI-Based Business Models in Manufacturing: Case Studies on Predictive Maintenance.
doi: 10.15488/11286
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Recent advances in Artificial Intelligence extend the boundaries of what machines can do in all industries and business sectors. The economic potential to apply AI in manufacturing results in an increasing number of companies striving to gain a competitive advantage through AI and move into new markets. In this context, particular importance is given to the predictive maintenance of machines. Predictive maintenance promises the possibility of avoiding unexpected machine downtimes and thus increasing the availability of production lines. However, only a few machine manufacturers have a marketable offering of AI-based products or services in their portfolio. Even if technical feasibility is proven, companies lack an understanding of how to integrate AI solutions into new Business Models. This paper thus presents three case studies and their Business Models as examples. Practical considerations and recommendations on the strategical adoption of predictive maintenance technologies are derived.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Bretones Cassoli, Beatriz ; Hoffmann, Felix ; Metternich, Joachim |
| Art des Eintrags: | Bibliographie |
| Titel: | Comparison of AI-Based Business Models in Manufacturing: Case Studies on Predictive Maintenance |
| Sprache: | Englisch |
| Publikationsjahr: | 2021 |
| Ort: | Hannover |
| Verlag: | publish-Ing |
| Buchtitel: | Proceedings of the Conference on Production Systems and Logistics : CPSL 2021 |
| DOI: | 10.15488/11286 |
| Kurzbeschreibung (Abstract): | Recent advances in Artificial Intelligence extend the boundaries of what machines can do in all industries and business sectors. The economic potential to apply AI in manufacturing results in an increasing number of companies striving to gain a competitive advantage through AI and move into new markets. In this context, particular importance is given to the predictive maintenance of machines. Predictive maintenance promises the possibility of avoiding unexpected machine downtimes and thus increasing the availability of production lines. However, only a few machine manufacturers have a marketable offering of AI-based products or services in their portfolio. Even if technical feasibility is proven, companies lack an understanding of how to integrate AI solutions into new Business Models. This paper thus presents three case studies and their Business Models as examples. Practical considerations and recommendations on the strategical adoption of predictive maintenance technologies are derived. |
| Freie Schlagworte: | Predictive Maintenance, Artificial Intelligence, Business Models, Machine Tools |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > Management industrieller Produktion |
| Hinterlegungsdatum: | 17 Apr 2023 07:00 |
| Letzte Änderung: | 17 Apr 2023 07:00 |
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