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.

Supporting Zero Defect Manufacturing Through Cloud Computing and Data Analytics: the Case Study of Electrospindle 4.0 / Leotta, F.; Mathew, J. G.; Mecella, M.; Monti, F.. - 451:(2022), pp. 119-125. (Intervento presentato al convegno CAiSE 2022 International Workshops tenutosi a Leuven; Belgium) [10.1007/978-3-031-07478-3_10].

Supporting Zero Defect Manufacturing Through Cloud Computing and Data Analytics: the Case Study of Electrospindle 4.0

Leotta F.
;
Mathew J. G.
;
Mecella M.
;
Monti F.
2022

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.
2022
CAiSE 2022 International Workshops
Artificial intelligence; Cloud computing; Industry 4.0; Zero defect manufacturing
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Supporting Zero Defect Manufacturing Through Cloud Computing and Data Analytics: the Case Study of Electrospindle 4.0 / Leotta, F.; Mathew, J. G.; Mecella, M.; Monti, F.. - 451:(2022), pp. 119-125. (Intervento presentato al convegno CAiSE 2022 International Workshops tenutosi a Leuven; Belgium) [10.1007/978-3-031-07478-3_10].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1643212
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