Industry 4.0 is nowadays the reference paradigm for production system implementation. The reasons lay in several motivations, among which the product/process data availability. This is paramount in supporting product tracking and tracing, feeding optimization applications, enabling sophisticated maintenance approaches and in monitoring resources and energy consumption in a sustainability perspective. While the setup of “green field” implementations is usually easier and well defined, problems arise when there is an existing system with physical shop-floor devices, applications and on-going production processes that cannot be disturbed or interrupted, and need to be interfaced. This paper is aiming to define an implementation strategy and a system architecture able to upgrade an existing production system to “Industry 4.0 compliant” status, keeping into account features and characteristics of said system, and applications without direct intervention (software or hardware) on the system and without perturbations of any on-going business. The proposed AI40A (Additive I40 Architecture) is structured on three basic components of: Data collection, Data transfer and Condition detection and trend forecasting. Each component and sub-module can be relocated individually on physical servers, cloud or edge computing virtual machines, based on availability or resources, computational needs or security reasons. As proof of concept, a prototype of the Additive Industry 4.0 Architecture that is implemented in Industry 4.0 Lab (I4.0Lab) of the School of Management of Politecnico di Milano in Bovisa (Milano) Campus will be shown. Two industrial applications are currently deployed on top of it: Production Rescheduling on Condition and Prognostic Maintenance based on Condition Regression with AR (Augmented Reality)

An “Additive” Architecture for Industry 4.0 Transition of Existing Production Systems

G. Tavola;A. Caielli;M. Taisch
2020

Abstract

Industry 4.0 is nowadays the reference paradigm for production system implementation. The reasons lay in several motivations, among which the product/process data availability. This is paramount in supporting product tracking and tracing, feeding optimization applications, enabling sophisticated maintenance approaches and in monitoring resources and energy consumption in a sustainability perspective. While the setup of “green field” implementations is usually easier and well defined, problems arise when there is an existing system with physical shop-floor devices, applications and on-going production processes that cannot be disturbed or interrupted, and need to be interfaced. This paper is aiming to define an implementation strategy and a system architecture able to upgrade an existing production system to “Industry 4.0 compliant” status, keeping into account features and characteristics of said system, and applications without direct intervention (software or hardware) on the system and without perturbations of any on-going business. The proposed AI40A (Additive I40 Architecture) is structured on three basic components of: Data collection, Data transfer and Condition detection and trend forecasting. Each component and sub-module can be relocated individually on physical servers, cloud or edge computing virtual machines, based on availability or resources, computational needs or security reasons. As proof of concept, a prototype of the Additive Industry 4.0 Architecture that is implemented in Industry 4.0 Lab (I4.0Lab) of the School of Management of Politecnico di Milano in Bovisa (Milano) Campus will be shown. Two industrial applications are currently deployed on top of it: Production Rescheduling on Condition and Prognostic Maintenance based on Condition Regression with AR (Augmented Reality)
Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future
978-3-030-27476-4
978-3-030-27477-1
Industry 4.0 - Integration - Additive architecture - 5G - IoT
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1118217
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