Stanula, Patrick ; Praetzas, Christopher ; Kohn, Oliver ; Metternich, Joachim ; Weigold, Matthias ; Buchwald, Arne (2020)
Stress-Oriented, Data-Based Payment Model for Machine Tools.
In: Procedia CIRP, (93)
doi: 10.1016/j.procir.2020.03.080
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
The acquisition costs of expensive machine tools are often a financial challenge for small and medium-sized enterprises, which is why many companies draw on traditional leasing models. For some types of machines, such as milling machines, however, there is no linear relationship between use and wear, thus creating a principle-agent problem and a potentially low(er) residual value of the machine in case of above-average use . Modern machine tools are increasingly equipped with sensors to monitor machining operations. The data from these sensors can help to deduce the wear of its components from the stress on the machine. Nevertheless, this has not resulted in data-driven, alternative payment models of expensive machines. Therefore, this paper presents a novel data-driven payment model based on a so -called stress factor, describing the aggregated machine wear due to the production process. This approach considers the economic and technologic perspectives to bring transparency to machine leasing.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2020 |
Autor(en): | Stanula, Patrick ; Praetzas, Christopher ; Kohn, Oliver ; Metternich, Joachim ; Weigold, Matthias ; Buchwald, Arne |
Art des Eintrags: | Bibliographie |
Titel: | Stress-Oriented, Data-Based Payment Model for Machine Tools |
Sprache: | Englisch |
Publikationsjahr: | 2020 |
Verlag: | Elsevier B.V. |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia CIRP |
(Heft-)Nummer: | 93 |
DOI: | 10.1016/j.procir.2020.03.080 |
Kurzbeschreibung (Abstract): | The acquisition costs of expensive machine tools are often a financial challenge for small and medium-sized enterprises, which is why many companies draw on traditional leasing models. For some types of machines, such as milling machines, however, there is no linear relationship between use and wear, thus creating a principle-agent problem and a potentially low(er) residual value of the machine in case of above-average use . Modern machine tools are increasingly equipped with sensors to monitor machining operations. The data from these sensors can help to deduce the wear of its components from the stress on the machine. Nevertheless, this has not resulted in data-driven, alternative payment models of expensive machines. Therefore, this paper presents a novel data-driven payment model based on a so -called stress factor, describing the aggregated machine wear due to the production process. This approach considers the economic and technologic perspectives to bring transparency to machine leasing. |
Freie Schlagworte: | business model, Machine tool, pay-per-x, remaining usefull lifetime |
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 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > Zerspanungstechnologie (2021 aufgegangen in TEC Fertigungstechnologie) |
Hinterlegungsdatum: | 11 Jan 2021 06:33 |
Letzte Änderung: | 11 Jan 2021 06:33 |
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