Optimization for a polymer reactor in petrochemical industry

The petrochemical industry plays a crucial role in the global economy, providing versatile products such as resins used in a wide range of quotidian applications. However, the complexity of multi-grade continuous production systems often results in significant operational inefficiencies, particularly in the form of "off-spec" or "non-prime" products during transitions between resin grades. This thesis addresses the challenge of optimizing sequencing and production planning for a polymer reactor within a second-generation petrochemical facility. A mixed-integer linear programming (MILP) model, introduced by the work of Abdullah, Shamayleh and Ndiaye, is implemented to minimize production and transition costs while satisfying customer demands. Real-world data from a leading Latin American petrochemical company are used to validate the model. The results demonstrate the model’s ability to reduce the number of transitions and associated costs compared to current practices. The study highlights the potential of mathematical modeling as a decision-support tool for improving efficiency and aligning production with market requirements in the petrochemical sector.