The evolution of grain size and component mechanical behaviour are fundamental aspects to analyse and control when manufacturing processes are considered. In this context, severe plastic deformation (SPD) processes, in which a high shear strain is imposed on the material, are recognized as the main techniques to achieve microstructural changes and material strengthening by the recrystallization, attracting both academic and industrial investigation activities. At the same time, nowadays, sustainable manufacturing design is one of the main responsibilities of the researchers looking at UN2030 agenda and the modern industrial paradigms. In this paper a new severe SPD process is proposed with the aim to steer manufacturing to fourth industrial revolution using some of Industry 4.0 pillars. In particular, additive manufacturing (AM) and numerical simulations were setup as controlling and monitoring techniques in manufacturing process of wires. Strengthening effect (yield and ultimate tensile strength, plasticity and hardness) and microstructural evolution (continuous dynamic recrystallization -CDRX-) due to severe plastic deformation were experimentally analysed and numerically investigated by an innovative finite element (FE) model able to validate the effectiveness of a properly modified process for ultra-fine aluminium alloy AA6101 wires production designed with the aim to avoid any post manufacturing costly thermal treatment. The study provides an accurate experimental study and numerical prediction of the thermo-mechanical and microstructural phenomena that occur during an advanced large plastic deformation process; it shows how the combination of smart manufacturing and simulations control represents the key to renew the traditional manufacturing methods in the perspective of the Industry 4.0, connecting and integrating the manufacturing process for the industrial evolution in production.

Sustainable manufacturing of ultra-fine aluminium alloy 6101 wires using controlled high levels of mechanical strain and finite element modeling

Filice L.
2021-01-01

Abstract

The evolution of grain size and component mechanical behaviour are fundamental aspects to analyse and control when manufacturing processes are considered. In this context, severe plastic deformation (SPD) processes, in which a high shear strain is imposed on the material, are recognized as the main techniques to achieve microstructural changes and material strengthening by the recrystallization, attracting both academic and industrial investigation activities. At the same time, nowadays, sustainable manufacturing design is one of the main responsibilities of the researchers looking at UN2030 agenda and the modern industrial paradigms. In this paper a new severe SPD process is proposed with the aim to steer manufacturing to fourth industrial revolution using some of Industry 4.0 pillars. In particular, additive manufacturing (AM) and numerical simulations were setup as controlling and monitoring techniques in manufacturing process of wires. Strengthening effect (yield and ultimate tensile strength, plasticity and hardness) and microstructural evolution (continuous dynamic recrystallization -CDRX-) due to severe plastic deformation were experimentally analysed and numerically investigated by an innovative finite element (FE) model able to validate the effectiveness of a properly modified process for ultra-fine aluminium alloy AA6101 wires production designed with the aim to avoid any post manufacturing costly thermal treatment. The study provides an accurate experimental study and numerical prediction of the thermo-mechanical and microstructural phenomena that occur during an advanced large plastic deformation process; it shows how the combination of smart manufacturing and simulations control represents the key to renew the traditional manufacturing methods in the perspective of the Industry 4.0, connecting and integrating the manufacturing process for the industrial evolution in production.
2021
Additive manufacturing
Dynamic recrystallization
Finite element modelling
Grain size
Industry 4.0
Smart manufacturing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/358170
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