A Predictive Multibody Model of Paper Applied to Cash Recycling

Despite the spread of digital payment systems, banknotes still play a vital role in the lives of people, financial institutions, and businesses. Automation is crucial in all cases where a large number of deposits/withdrawals need to be handled. In spite of the large number of cash recyclers worldwide and their continuous evolution, one of the most significant parts of their design, i.e., the interaction with banknotes, is still predominantly based on a lengthy iterative process that includes testing. This has detrimental effects not only on time-to-market but also on the costs and on the willingness to explore multiple design solutions, thus potentially reducing the quality of the final product. The testing phase is made necessary by the lack of an effective and predictive model for the banknote and of its contact with the components of the cash recycler. The purpose of this work is to bridge this gap in the literature by introducing and validating an original multibody model of the banknote-cash recycler system. The proposed approach includes the possibility of including the nonlinear orthotropic paper material curves and of customizing quantities such as paper thickness and friction coefficients at specific locations, with potential applications in optimizing banknote validation, reducing wear in cash handling systems, and improving the design of next-generation cash recyclers.