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between seemingly similar batches. Instead, the model is reduced to a minimal set of parameters, which can be recovered from measurement data via least-square fits as outlined in Section 3. The examples presented in Section 4, taken from ongoing research, illustrate the possibility in principle of applying the model to real-world data. Detailed analysis of the optimal application of the model, including optimal selection of sample points and the achievable measurement uncertainty, remain open for future research. While the model-based approach is applicable with only a minimal set of sensors, it trades those savings in hardware cost for an increased computational load. An efficient implementation of the necessary algorithms is crucial for any practical application, and even then, a real-time evaluation of every single corrugated board produced may not be feasible. Moreover, any model-based approach requires that the model assumptions are satisfied. Sharp bends in the board, for example, would most likely yield unpredictable results, as this is not included in the model. Furthermore, the board should not be too small, since the model neglects border effects. In regard to controlling warp in production, Section 2.4 derives the necessary condition for warp-free board. It is shown that, in theory, an infinite number of possible solutions to correct any given form of warp exists. This opens up the possibility of considering other criteria relevant in industrial corrugated board production, such as energy consumption and production speed. Supplementary Materials: The data displayed in Figure 5 is available online at https://www.mdpi. com/article/10.3390/app12031684/s1 as MATLAB files. Author Contributions: Conceptualization, G.F. and M.B.; methodology, M.B.; software, M.B.; formal analysis, M.B.; writing—original draft preparation, M.B.; writing—review and editing, G.F. and M.B.; visualization, M.B.; supervision, G.F.; project administration, G.F.; funding acquisition, G.F. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the ZIM Program (Grant ZF4152307PO8) by the German Federal Ministry for Economic Affairs and Energy. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—491183248. Funded by the Open Access Publishing Fund of the University of Bayreuth. This Project is supported by the Federal Ministry for Economic Affairs and Energy (BMWi) on the basis of a decision by the German Bundestag. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are available in Supplementary Material. Conflicts of Interest: The authors declare no conflict of interest.
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