An optimization framework for scheduling of converter aisle operation in a nickel smelting plant

The scheduling of converter aisle operation in a nickel smelting plant is a complex task with significant ramifications to plant profitability and production. An optimization-based scheduling formulation is developed using a continuous-time paradigm to accurately represent event timings. The formulation accounts for environmental restrictions on sulfur dioxide emissions, using event timing constraints. Flash furnaces are characterized by a continuous inlet flow and intermittent, discrete material removal, which is captured via novel semi-continuous modeling. An innovative sequencing and symmetry-breaking scheme is introduced to exploit identical units operating in parallel. A rolling horizon feature is included to accommodate real-time optimization. Tightening constraints are developed to improve the computational performance. A unique, multi-tiered procedure enhances the practicality of the solution and supports additional operability objectives, without compromising the optimality of the primary objective. The success of the approach is demonstrated via case studies arising from industrial production scenarios.