Issue |
Manufacturing Rev.
Volume 9, 2022
|
|
---|---|---|
Article Number | 18 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/mfreview/2022017 | |
Published online | 04 July 2022 |
Research Article
A method for yield and cycle time improvements in Al alloy casting with enhanced conductivity steel for die construction
1
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Via Pietro Vivarelli 10, 41125 Modena Italy
2
Bonomi Acciai, Via Industriale 90, 25065 Lumezzane, Italy
3
IMS Technologies, Via Cav. Beretta 25, 24050 Calcinate, Italy
* e-mail: alberto.vergnano@unimore.it
Received:
18
January
2022
Accepted:
26
May
2022
A die for Al alloy casting must be designed to achieve the expected quality levels. Moreover, the casting unit cost must be regarded as the objective function to be minimised. It can be expressed as a function of the quantity of materials and energy to be used, cycle time and equipment investment. This work compares the performance of the die with inserts manufactured using the usual 1.2343 steel with that of the innovative 1.2383. The latter is considered due to its enhanced thermal conductivity, despite being more expensive. Simulation experiments are designed to evaluate different die layouts. The quality design solutions are evaluated against the cost objective function in order to identify the optimal die choice. A case study on gravity die casting (GDC) of an AlSi7Mg0.3 engine head shows faster solidification dynamics when using 1.2383 instead of 1.2343 steel. This reduces the feeder volume, thus increasing the production yield and speeding up the cycle time with a leverage effect. The higher investment cost for the inserts is rapidly returned thanks to the reduction in variable costs. The Return On Investment (ROI) with the improved die in the new solution is short compared with the life of the die.
Key words: Gravity die casting / cost optimisation / material selection / steel conductivity / cycle time / process yield
© A. Vergnano et al., Published by EDP Sciences 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.