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
Article, Bibliographie
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.
| Item Type: | Article |
|---|---|
| Erschienen: | 2020 |
| Creators: | Stanula, Patrick ; Praetzas, Christopher ; Kohn, Oliver ; Metternich, Joachim ; Weigold, Matthias ; Buchwald, Arne |
| Type of entry: | Bibliographie |
| Title: | Stress-Oriented, Data-Based Payment Model for Machine Tools |
| Language: | English |
| Date: | 2020 |
| Publisher: | Elsevier B.V. |
| Journal or Publication Title: | Procedia CIRP |
| Issue Number: | 93 |
| DOI: | 10.1016/j.procir.2020.03.080 |
| 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. |
| Uncontrolled Keywords: | business model, Machine tool, pay-per-x, remaining usefull lifetime |
| Divisions: | 16 Department of Mechanical Engineering 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > Management of Industrial Production 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > Machining Technology (2021 merged in TEC Fertigungstechnologie) |
| Date Deposited: | 11 Jan 2021 06:33 |
| Last Modified: | 11 Jan 2021 06:33 |
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