TY - GEN
T1 - Melting Efficiency in Secondary Aluminum Foundry Application
AU - Chiloane-Nkomo, Khutsiso R.
AU - Eboule, Patrick S.Pouabe
AU - Pretorius, Jan Harm C.
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This study was conducted in the secondary aluminum smelting plant, which creates a variety of aluminum oxidizers. The current average daily production is 21 tons. Increasing the production to 31 tons per day could improve melting efficiency at the foundry. Melting efficiency is also affected by the melt loss produced during melting, which is significantly higher (14%-18%) in the Reverberatory Furnace (RF) with a 9.5-ton capacity. This research intended to optimize the melting losses to 8-10% (melt loss), as assessed by the following variables: temperature control, charging sequence, charge make-up, fluxing, and dross press procedure. Using secondary data for casting production of nuggets, multiple regression models were created using IBM SPSS Statistics. Using ideal factors such as furnace capacity consumption, flux usage, and dross generated during the melting process, multiple regression models were utilized to calculate the melting loss. Data was collected following the implementation of the trials, analyzed using primary and secondary data, and then subjected to multiple regression analysis. This was done to determine the impact of operational practice variables on melting efficiency and melting loss. Melt loss was diminished by reducing dross production, tap temperature, and charging/melting time, adding flux, running the furnace at full capacity, applying continuous melting, and using old roll (O/R), CANS, WIRE; extrusions (EXT), O/R, high purity aluminum (P/A), and O/R, P/A charge make-up.
AB - This study was conducted in the secondary aluminum smelting plant, which creates a variety of aluminum oxidizers. The current average daily production is 21 tons. Increasing the production to 31 tons per day could improve melting efficiency at the foundry. Melting efficiency is also affected by the melt loss produced during melting, which is significantly higher (14%-18%) in the Reverberatory Furnace (RF) with a 9.5-ton capacity. This research intended to optimize the melting losses to 8-10% (melt loss), as assessed by the following variables: temperature control, charging sequence, charge make-up, fluxing, and dross press procedure. Using secondary data for casting production of nuggets, multiple regression models were created using IBM SPSS Statistics. Using ideal factors such as furnace capacity consumption, flux usage, and dross generated during the melting process, multiple regression models were utilized to calculate the melting loss. Data was collected following the implementation of the trials, analyzed using primary and secondary data, and then subjected to multiple regression analysis. This was done to determine the impact of operational practice variables on melting efficiency and melting loss. Melt loss was diminished by reducing dross production, tap temperature, and charging/melting time, adding flux, running the furnace at full capacity, applying continuous melting, and using old roll (O/R), CANS, WIRE; extrusions (EXT), O/R, high purity aluminum (P/A), and O/R, P/A charge make-up.
KW - Melting techniques
KW - Multiple Regression
KW - Operational practice variables
KW - melting loss
UR - https://www.scopus.com/pages/publications/105017795839
U2 - 10.1109/ICTAS64866.2025.11155507
DO - 10.1109/ICTAS64866.2025.11155507
M3 - Conference contribution
AN - SCOPUS:105017795839
T3 - 2025 Annual IEEE Conference on Information Communication Technology and Society, ICTAS 2025 - Proceedings
BT - 2025 Annual IEEE Conference on Information Communication Technology and Society, ICTAS 2025 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 Annual IEEE Conference on Information Communication Technology and Society, ICTAS 2025
Y2 - 23 July 2025 through 25 July 2025
ER -