Optimal planning and feedstock-mix selection for multiproduct polymer production

•Manufacture of multiple polymer grades in a polypropylene production facility is addressed.•Single and multiple product NLP formulations are presented for production planning.•The trade-off between feedstocks costs and production rates is considered.•Proposed formulation has been implemented with user-friendly computer interface. In this paper, we describe a nonlinear programming model to determine the optimal balance of feedstocks to manufacture multiple polymer grades in a polypropylene production facility. The main units of the process are a distillation column and a polymerization reactor, for which accurate short-cut process models were developed. Both a single and multiple product formulations are presented. The proposed models seek to maximize the plant throughput while minimizing the production costs. The possibility of adding extra production is also considered. The formulations are applied to several case studies, both to analyze the performance of the model and to illustrate its potential economic impact. The trade-off between feedstocks costs and production rates is analyzed by solving the multiple-product model with different time horizons. An annualized-slate long term case study is presented. The proposed formulation with a user-friendly interface has been deployed to assist with commercial and operation decisions at the plant.