Zero Defect Manufacturing (ZDM) is an emergent and disruptive paradigm that aims to optimize industrial process efficiency and sustainability by leveraging innovative and sophisticated data-driven approaches. It is a technology intensive concept that has the ambition of achieving and maintaining "first-time-right'' quality goals in spite of varying processes and input material. As a result, developing ZDM applications might become overwhelming for small enterprises due to the multitude of diverse platform, the lack of know-how, and the need to adapt general purpose solutions to meet their needs. The Big Data Innovation and Research Excellence (Bi-Rex) is an Italian consortium that aims to accelerate the industrial innovation process of small enterprises. Within this consortium we developed a Big Data platform that enables adaptive analytics at the IT/OT boundary by leveraging innovative solutions for the safe and automatic deployment of data-driven apps, using MLOps and DevOps techniques and technologies, and evaluated it in real use cases provided by the world leading industrial partners involved in the project.

Enabling adaptive analytics at the edge with the Bi-Rex Big Data platform

Venanzi R.
Primo
;
Dahdal S.
Secondo
;
Tortonesi M.;Stefanelli C.
Ultimo
2023

Abstract

Zero Defect Manufacturing (ZDM) is an emergent and disruptive paradigm that aims to optimize industrial process efficiency and sustainability by leveraging innovative and sophisticated data-driven approaches. It is a technology intensive concept that has the ambition of achieving and maintaining "first-time-right'' quality goals in spite of varying processes and input material. As a result, developing ZDM applications might become overwhelming for small enterprises due to the multitude of diverse platform, the lack of know-how, and the need to adapt general purpose solutions to meet their needs. The Big Data Innovation and Research Excellence (Bi-Rex) is an Italian consortium that aims to accelerate the industrial innovation process of small enterprises. Within this consortium we developed a Big Data platform that enables adaptive analytics at the IT/OT boundary by leveraging innovative solutions for the safe and automatic deployment of data-driven apps, using MLOps and DevOps techniques and technologies, and evaluated it in real use cases provided by the world leading industrial partners involved in the project.
2023
Venanzi, R.; Dahdal, S.; Solimando, M.; Campioni, L.; Cavalucci, A.; Govoni, M.; Tortonesi, M.; Foschini, L.; Attana, L.; Tellarini, M.; Stefanelli, C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2533451
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