Researchers Catch-up hosted online from Curtin University
Friday 25 September 2020
In any asset-intensive industry, maintenance activities are inevitable and costly, and hence it is essential to investigate better ways of scheduling maintenance activities. Conducting maintenance may require certain parts of the plant or the whole plant to be shut down, which usually leads to large financial loss. Therefore, optimal scheduling of maintenance activities is highly desirable as it will potentially reduce downtime and increase profitability. However, since the plant is a complex interconnected network of sub-systems, it is extremely challenging to optimize maintenance schedules and provide synergistic opportunities for sharing utilities, manpower, and minimizing travel between locations. Moreover, the timing of maintenance shutdowns may be affected by external factors, such as production planning, inventory management and even market demands, which make maintenance scheduling problems even more challenging to tackle. In this research, mathematical optimization models will be developed to minimize the total cost, and maximize synergies and profits in maintenance operations. Since the models are difficult to solve for large-scale data sets, we will develop new mathematical methods and novel algorithms to reduce dimensionality and solve the models more efficiently. Furthermore, the proposed models and algorithms will be implemented in optimization software using real data provided by mining companies. The expected outcomes of this research will enable planners in the mining industry to build optimal maintenance schedules and shutdown plans, which will bring large financial benefits to the industry https://ctmtds.atlassian.net/wiki/x/VgA6AQ