This thesis explores the optimization of the sheet metal deep drawing process using a simulation-based approach to reduce material waste and improve manufacturing sustainability. Simulations in Simufact Forming software 2024 tested variations in press speed, blank holder force, die geometry, and material properties. Defects such as necking and wrinkling are to be minimized. The study demonstrates that simulation significantly enhances efficiency, accuracy, and cost-effectiveness compared to traditional methods. Thus helping us get a manufacturing process which can be more sustainable and environment friendly.
This thesis explores the optimization of the sheet metal deep drawing process using a simulation-based approach to reduce material waste and improve manufacturing sustainability. Simulations in Simufact Forming software 2024 tested variations in press speed, blank holder force, die geometry, and material properties. Defects such as necking and wrinkling are to be minimized. The study demonstrates that simulation significantly enhances efficiency, accuracy, and cost-effectiveness compared to traditional methods. Thus helping us get a manufacturing process which can be more sustainable and environment friendly.
optimization of sheet metal production process for sustainable manufacturing (simulation approach)
JAMES, JUSTINE
2024/2025
Abstract
This thesis explores the optimization of the sheet metal deep drawing process using a simulation-based approach to reduce material waste and improve manufacturing sustainability. Simulations in Simufact Forming software 2024 tested variations in press speed, blank holder force, die geometry, and material properties. Defects such as necking and wrinkling are to be minimized. The study demonstrates that simulation significantly enhances efficiency, accuracy, and cost-effectiveness compared to traditional methods. Thus helping us get a manufacturing process which can be more sustainable and environment friendly.| File | Dimensione | Formato | |
|---|---|---|---|
|
JAMES_JUSTINE.pdf
accesso aperto
Dimensione
3.01 MB
Formato
Adobe PDF
|
3.01 MB | Adobe PDF | Visualizza/Apri |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
https://hdl.handle.net/20.500.12608/94813