Issue |
Matériaux & Techniques
Volume 108, Number 1, 2020
|
|
---|---|---|
Article Number | 101 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/mattech/2020013 | |
Published online | 07 April 2020 |
Regular Article
Optimization of manufacturing copper-graphite composite for electrical contact applications using grey relational analysis
Department of Metallurgical Engineering, University of Babylon,
Hilla
51001, Iraq
* e-mail: alaahus30@gmail.com
Received:
12
March
2019
Accepted:
5
March
2020
Copper-graphite composite is one of the most important copper based composites, which is used, widely in electrical applications due to its excellent conductivity and high wear resistant. In this work, an attempt has been made to improve the multi-performance characteristics of copper graphite composite prepared by powder metallurgy and increase its expected life by optimizing the manufacturing process of this composite using statistical method. The experiments were carried out under various conditions of compacting pressure, sintering temperature and graphite content based on L9 orthogonal array. The experimental results indicated that multi-performance characteristics of the prepared composite such as electrical conductivity, densification and wear rate are influenced significantly by the studied parameters and the optimal process parameters level for optimum multi-performance characteristics was obtained in a compaction pressure of 750 MPa, sintering temperature of 950 °C and 10 Vol.-% of graphite content.
Key words: copper-graphite composite / grey relational analysis / wear rate / densification / electrical conductivity
© SCF, 2020
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.