Abstract
Industry 4.0 represents the last evolution of manufacturing. With respect to Industry 3.0, which introduced the digital interconnection of machinery with monitoring and control systems, the fourth industrial revolution extends this concept to sensors, products and any kind of object or actor (thing) involved in the process. The tremendous amount of data produced is intended to be analyzed by applying methods from artificial intelligence, machine learning and data mining. One of the objective of such an analysis is Zero Defect Manufacturing, i.e., a manufacturing process where data acquired during the entire life cycle of products is used to continuously improve the product design in order to provide customers with unprecedented quality guarantees. In this paper, we discuss the design choices behind a Zero Defect Manufacturing system architecture in the specific use case of spindle manufacturing.
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Acknowledgements
This work has been supported by the Italian MISE project Electrospindle 4.0 (id: F/160038/01-04/X41).
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Leotta, F., Mathew, J.G., Mecella, M., Monti, F. (2022). Supporting Zero Defect Manufacturing Through Cloud Computing and Data Analytics: the Case Study of Electrospindle 4.0. In: Horkoff, J., Serral, E., Zdravkovic, J. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2022. Lecture Notes in Business Information Processing, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-031-07478-3_10
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