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Publication type
Journal articleAuthor
Stanula, PatrickPraetzas, Christopher
Kohn, Oliver
Metternich, Joachim
Weigold, Matthias
Buchwald, Arne
Publication Year
2020Journal
Procedia CIRPPublication Volume
93Publication Issue
2020Publication Begin page
1526Publication End page
1531
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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.Knowledge Domain/Industry
Operations & Supply Chain Managementae974a485f413a2113503eed53cd6c53
10.1016/j.procir.2020.03.080