The goal of the MICS (Made in Italy, Circular and Sustainable) project is to develop new models and techniques to support the entire pipeline for applying Data Science algorithms to data from industrial processes. Although many libraries and tools are already available to aid the analysis of data, we believe that each different application domain requires individual study to propose appropriate methods and tools that accommodate the specific peculiarities of its data. In this position paper, we discuss the following points by also outlining our case studies.

The MICS Project: A Data Science Pipeline for Industry 4.0 Applications

Cristaldi, Loredana;Esmaili, Parisa;Gruosso, Giambattista;Bella, Alessio La;Scattolini, Riccardo;Tanca, Letizia
2023-01-01

Abstract

The goal of the MICS (Made in Italy, Circular and Sustainable) project is to develop new models and techniques to support the entire pipeline for applying Data Science algorithms to data from industrial processes. Although many libraries and tools are already available to aid the analysis of data, we believe that each different application domain requires individual study to propose appropriate methods and tools that accommodate the specific peculiarities of its data. In this position paper, we discuss the following points by also outlining our case studies.
2023
2023 IEEE International Workshop on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023 - Proceedings
digital factories, data management, machine learning pipeline, case study
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1260903
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