Decomposition-Coordination Optimization for Copper Smelting Process : Optimizing and Enhancing Process Efficiency
Ahmed, Hussain (2024)
Ahmed, Hussain
Tampere University
2024
Teknisten tieteiden tohtoriohjelma - Doctoral Programme in Engineering Sciences
Tekniikan ja luonnontieteiden tiedekunta - Faculty of Engineering and Natural Sciences
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Väitöspäivä
2024-08-23
Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-03-3556-4
https://urn.fi/URN:ISBN:978-952-03-3556-4
Tiivistelmä
The copper industry is confronted with a compelling need to enhance throughput and reduce copper losses during the copper production process. Recovery of these losses requires additional treatment, which escalates production costs and demands extra investments. One apparent strategy to diminish the impact of these copper losses during the production process is to increase the use of high-quality copper ores. However, the current copper industry trend indicates the depletion of such ores, making this option less viable. Consequently, the adoption of low-quality copper ores has become a common practice, leading to increased production costs and reduced copper production, highlighting the importance of minimizing copper losses in the copper production process.
Within the copper smelting process, the Flash Smelting Furnace (FSF) and Peirce-Smith Converters (PSCs) contribute substantially to copper losses, which depends on the scheduling of internal operations within the PSCs and the scheduling of the FSF and PSC units. Designing an automatic scheduling solution for FSF and PSC units that can reduce copper losses during production proves challenging due to the conflicting intricate inter-dependencies among these units. These conflicting inter-dependencies arise from the material storage capacity of the FSF unit, crane movement for loading raw material to the PSC units, and gas-handling capacity of the pipes, which are shared by the FSF and PSC units. Consequently, operating and scheduling FSF and PSC units without considering these inter-dependencies shifts the smelter from an optimal to a sub-optimal operational point. Therefore, there is a need for a novel scheduling framework that minimizes copper losses, resolves process inter-dependencies, and operates the process at optimal operating points.
To automate the scheduling of the copper smelting process that consists of FSF and multiple PSC units, this study develops novel optimization-based centralized and hierarchical scheduling frameworks using discrete time to precisely represent process operation timings. These frameworks account for FSF storage limits, gas pipeline capacity constraints, and matte trans- fer between the FSF and PSC units. An efficient scheme is proposed to minimize copper losses in the PSC unit, leveraging process dynamics. For the hierarchical scheduling framework, this thesis introduces novel heuristics-based coordination strategies. The coordination strategy based on hard heuristics pauses a processing unit to resolve scheduling inter-dependencies, while the strategy utilizing soft heuristics turns the scheduling problem into an economic re- source allocation problem where it uses proportional-integral controllers to calculate prices, aiding processing units in independently resolving their conflicting inter-dependencies. Additionally, this thesis provides a comprehensive analysis of the proposed scheduling frameworks, evaluating their adaptability under various operating conditions.
Within the copper smelting process, the Flash Smelting Furnace (FSF) and Peirce-Smith Converters (PSCs) contribute substantially to copper losses, which depends on the scheduling of internal operations within the PSCs and the scheduling of the FSF and PSC units. Designing an automatic scheduling solution for FSF and PSC units that can reduce copper losses during production proves challenging due to the conflicting intricate inter-dependencies among these units. These conflicting inter-dependencies arise from the material storage capacity of the FSF unit, crane movement for loading raw material to the PSC units, and gas-handling capacity of the pipes, which are shared by the FSF and PSC units. Consequently, operating and scheduling FSF and PSC units without considering these inter-dependencies shifts the smelter from an optimal to a sub-optimal operational point. Therefore, there is a need for a novel scheduling framework that minimizes copper losses, resolves process inter-dependencies, and operates the process at optimal operating points.
To automate the scheduling of the copper smelting process that consists of FSF and multiple PSC units, this study develops novel optimization-based centralized and hierarchical scheduling frameworks using discrete time to precisely represent process operation timings. These frameworks account for FSF storage limits, gas pipeline capacity constraints, and matte trans- fer between the FSF and PSC units. An efficient scheme is proposed to minimize copper losses in the PSC unit, leveraging process dynamics. For the hierarchical scheduling framework, this thesis introduces novel heuristics-based coordination strategies. The coordination strategy based on hard heuristics pauses a processing unit to resolve scheduling inter-dependencies, while the strategy utilizing soft heuristics turns the scheduling problem into an economic re- source allocation problem where it uses proportional-integral controllers to calculate prices, aiding processing units in independently resolving their conflicting inter-dependencies. Additionally, this thesis provides a comprehensive analysis of the proposed scheduling frameworks, evaluating their adaptability under various operating conditions.
Kokoelmat
- Väitöskirjat [4891]