Optimal Converter Aisle Scheduling in a Nickel Smelting Plant

The manual scheduling of operations in a Converter Aisle for Nickel Smelting is both a time-consuming and tedious task. The challenge of manually scheduling this process involves several tasks on multiple units (such as tapping of matte from furnaces, charging of converters, blowing, and skimming slag from converters). Furthermore, these tasks need to be carried out subject to a number of operational constraints that include upper and lower matte level limits in the furnaces, and the number and timing of the blowing operations required for a converter batch. This already complex set of tasks is further complicated by emission limits, which places additional constraints on the Converter Aisle operation. However, when process disruptions invalidate the nominal schedule, it falls on operators to rely on operating protocols and experience to navigate the process operations and obey operating constraints as best as possible. These considerations motivate the development and use of an optimal scheduling decision support system that is capable of timely process scheduling, while respecting operational constraints, to achieve a given objective. The work presented formulates the operation scheduling as a mathematical optimization problem, where the relationships between the material flows, compositions, operating procedures, event timing and various constraints are captured, and the optimization objectives are quantified. The problem is expressed in a standard mathematical form that is amenable to solution using commercial optimization software. The project explores optimization opportunities in order to identify optimal scheduling configurations that are not realizable based on human intuition due to the complexity inherent in the process.