Stochastic supply chain optimization for ammonia and urea processes

Abstract

To support the demand growth in the agriculture sector from increasing population, ammonia and urea productions have been continuously increasing. Methane from natural gas can be used as feedstock in the production process. Nevertheless, the conventional plant using natural gas feedstock produces carbon dioxide as a by-product of the process. This proposed plant contains two processes, producing ammonia and urea can be more efficient in the production, where the byproducts of CO₂ can be used to produce more urea and reduce CO₂ emission. This research proposes ammonia and urea synthesis process using PROII software to simulate workflow and estimate the energy consumption. To be marketable and profitable for the agricultural industry, the techno-economic and stochastic analysis are applied to deal with uncertain demand from the market. This work is comprised of three main parts; the first part is the simulation of the base case process of the proposed ammonia/urea plant. The input data and parameters are obtained from the petrochemical industry in Thailand. In the second part, techno-economic analysis is significant for a feasibility study to estimate expenditure and the profitability of the project. Finally, the stochastic analysis is applied to optimize the production rate and supply chain of the products from various demands of the markets. The optimized supply chain network has been investigated on the production rate, the effect of penalty, and profit feasibility through profit accumulative curve. The conceptual design of manufacturing processes attempts to produce ammonia and urea, based on 1,930 t/d of natural gas feedstock.