Abstract
Copper losses during the Peirce-Smith converter (PSC) operation is of great concern in the copper smelting process. Two primary objectives of the PSC are to produce blister copper with a shorter batch time and to keep the copper losses at a minimum level. Due to the nature of the process, those two objectives are contradictory to each other. Moreover, actions inside the PSC are subject to several operational constraints that make it difficult to develop a scheduling framework for its optimal operation. In this work, a basic but efficient linear multi-period scheduling framework for the PSC is presented that finds the optimal timings of the PSC operations to keep the copper losses and the batch time at a minimum level. An industrial case study is used to illustrate the effectiveness of the proposed framework. This novel solution can be implemented in other smelting processes and used for the design of an inter-PSC scheduling framework.
Highlights
More than 60% of the concentrates come from low-grade deposits that have a high fraction of impurities [4,5]. This utilization of low quality concentrates leads to higher operational costs in terms of copper losses, which remain a part of the slag as waste
Since the copper losses depend on the matte grade value, the copper loss trajectory in the slag can be estimated as a function of time t using the results presented in [13]
This paper presents a linear dynamic mixed-integer linear programming (MILP)-based scheduling model for the Peirce-Smith converter (PSC) in the smelting process
Summary
The copper industry is one of the backbones of the European processing industry, representing more than 12% of the worldwide production of refined copper [1] This industry can utilize both high and low quality concentrates for its operation. More than 60% of the concentrates come from low-grade deposits that have a high fraction of impurities (e.g., arsenic and bismuth) [4,5] This utilization of low quality concentrates leads to higher operational costs in terms of copper losses, which remain a part of the slag as waste. These include minimizing slag generation, minimizing copper entrainment in the slag, and pyrometallurgical slag reduction These strategies depend on the chemical nature of the process, and sometimes they cannot be adopted because of limitations in the quality of the concentrate, quality requirements, and other operational constraints.
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