Abstract
In this paper, we present a new method based on Network Analysis for implementing what we called Sensorless Predictive Maintenance (PdM) on production lines of coffee machines of an Italian manufacturing company, Nuova Simonelli S.p.A.. To the best of our knowledge, such an approach is an innovative one in the field of PdM; its final goal is to implement a way for performing PdM without installing sensors on machines or production lines. The results are very promising and allow us to gain knowledge about the assembly process after it took place. Then, such knowledge can be used for improving the process and putting into practice the Sensorless PdM on the new coffee machines.
The Authors thank Nuova Simonelli S.p.A. for sharing data.
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References
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.-U.: Complex networks: structure and dynamics. Phys. Rep. 424(4), 175–308 (2006)
Corradini, F., Luciani, C., Morichetta, A., Piangerelli, M., Polini, A.:
a dissimilarity measure for public administration process logs. In: Scholl, H.J., Gil-García, J.R., Janssen, M., Kalampokis, E., Lindgren, I., Rodríguez Bolívar, M.P. (eds.) EGOV 2021. LNCS, vol. 12850, pp. 301–314. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-84789-0_22Jossen, S.: The world’s most valuable resource is no longer oil, but data. The Economist (2017)
Khokhar, D.: Gephi Cookbook. Packt Publishing, Birmingham (2015)
Li, X., Liu, X., Yue, C., Liang, S.Y., Wang, L.: Systematic review on tool breakage monitoring techniques in machining operations. Int. J. Mach. Tools Manuf. 176, 103882 (2022)
Luján-Mora, S., Trujillo, J., Song, I.-Y.: Extending the UML for multidimensional modeling. In: Jézéquel, J.-M., Hussmann, H., Cook, S. (eds.) UML 2002. LNCS, vol. 2460, pp. 290–304. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45800-X_23
Manyika, J., Chui, M., Bisson, P., Woetzel, J.R., Dobbs, R., Bughin, J., Aharon, D.: The internet of things: mapping the value beyond the hype. Technological innovation (2015)
Mehmood, N.Q., Culmone, R., Mostarda, L.: Modeling temporal aspects of sensor data for MongoDB NoSQL database. J. Big Data 4(1), (2017)
Merelli, E., Piangerelli, M., Rucco, M., Toller, D.: A topological approach for multivariate time series characterization: the epileptic brain. In: Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS) (2016)
Object Managemt Group. About the Unified Modeling Language Specification Version 2.5.1 (2017)
a dissimilarity measure for public administration process logs. In: Scholl, H.J., Gil-García, J.R., Janssen, M., Kalampokis, E., Lindgren, I., Rodríguez Bolívar, M.P. (eds.) EGOV 2021. LNCS, vol. 12850, pp. 301–314. Springer, Cham (2021). Author information
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Cacciagrano, D., Corradini, F., Piangerelli, M. (2023). Sensorless Predictive Maintenance: An Example on a ‘Not 4.0’ Coffee Machine Production Process. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2023. Lecture Notes in Networks and Systems, vol 655. Springer, Cham. https://doi.org/10.1007/978-3-031-28694-0_29
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DOI: https://doi.org/10.1007/978-3-031-28694-0_29
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