Inventory management for preventive and corrective maintenance under supply chain risks.

In production plants which require preventive and corrective maintenance, inventory management can help ensure that there are sufficient spare parts available for the maintenance to be performed. It can be costly to order and hold spare stock, and it is also expensive to shut down a piece of machinery due to not having enough spare parts for it to be fixed; therefore, it is ideal to have a balance between ordering more units than necessary and not ordering enough units to fit the demand. Some difficulties to consider, however, are that units inside each machine break unpredictably and each unit must be ordered well in advance to be in-stock, so it is impossible to know the number of spare parts necessary to order to exactly meet the future stochastic demand. This project focuses on finding the optimal inventory and maintenance decisions that help minimise expected future costs. These decisions also improve environmental outcomes by not over-ordering stock and by conducting maintenance in a timely manner.
By determining the optimal solutions for small instances of this problem, we can derive and understand their mathematical properties. However, determining optimal decisions becomes more complicated and potentially infeasible for larger instances with many machines and material types, as exact solution methods will take too long to run. We therefore use the insights about mathematical properties to develop novel heuristic methods, i.e. methods which produce solutions close to optimality.

In partnership with Shell.