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    Stress-oriented, data-based payment model for machine tools

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    Publication type
    Journal article
    Author
    Stanula, Patrick
    Praetzas, Christopher
    Kohn, Oliver
    Metternich, Joachim
    Weigold, Matthias
    Buchwald, Arne
    Publication Year
    2020
    Journal
    Procedia CIRP
    Publication Volume
    93
    Publication Issue
    2020
    Publication Begin page
    1526
    Publication End page
    1531
    
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    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.
    Keyword
    Business Model, Pay-Per-X, Machine Tool, Remaining Usefull Lifetime
    Knowledge Domain/Industry
    Operations & Supply Chain Management
    DOI
    10.1016/j.procir.2020.03.080
    URI
    http://hdl.handle.net/20.500.12127/6570
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.procir.2020.03.080
    Scopus Count
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