Recent advances in the manufacturing industry have paved the way for a systematical deployment and implementation of systems, including Cyber-Physical Systems (CPS) and smart tools, aimed at reaching Zero Defect Manufacturing (ZDM). Nowadays, ZDM strategies are easier to be implemented due to the availability of the required amount of data coming from the distributed sensor network architectures of the production systems. Such a trend is transforming the manufacturing industry to the next generation, namely Industry 4.0. In this context, there is an urgent need to identify and adopt effective quality controls to be performed on the products. This paper proposes a probabilistic model that can be used to evaluate quality inspection effectiveness, i.e., the ability to identify product defects. This model, which integrates perfectly within the current modern manufacturing context, can act as a support tool for decision making and guide designers toward zero-defect strategies.

Towards Zero Defect Manufacturing: probabilistic model for quality control effectiveness / Verna, Elisa; Genta, Gianfranco; Galetto, Maurizio; Franceschini, Fiorenzo. - ELETTRONICO. - (2021), pp. 522-526. ((Intervento presentato al convegno 2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) tenutosi a Virtual Conference nel June 7-9, 2021 [10.1109/MetroInd4.0IoT51437.2021.9488487].

Towards Zero Defect Manufacturing: probabilistic model for quality control effectiveness

Verna, Elisa;Genta, Gianfranco;Galetto, Maurizio;Franceschini, Fiorenzo
2021

Abstract

Recent advances in the manufacturing industry have paved the way for a systematical deployment and implementation of systems, including Cyber-Physical Systems (CPS) and smart tools, aimed at reaching Zero Defect Manufacturing (ZDM). Nowadays, ZDM strategies are easier to be implemented due to the availability of the required amount of data coming from the distributed sensor network architectures of the production systems. Such a trend is transforming the manufacturing industry to the next generation, namely Industry 4.0. In this context, there is an urgent need to identify and adopt effective quality controls to be performed on the products. This paper proposes a probabilistic model that can be used to evaluate quality inspection effectiveness, i.e., the ability to identify product defects. This model, which integrates perfectly within the current modern manufacturing context, can act as a support tool for decision making and guide designers toward zero-defect strategies.
978-1-6654-1979-6
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2905992