Dynamic Simulation for Verification of Gains with the Implementation of Advanced Process Control for a Nickel Sulphide Ore Beneficiation Plant

Abstract

A dynamic simulation tool was used to quantify the benefits from the implementation of an advanced control system for a low grade Nickel sulphide ore beneficiation plant. In order to obtain a consistency between the simulation and the process a database that represented the natural variability of the ore was used. The information consisted of laboratory analyzes every 2 hours for the concentrations of nickel in the feed, product and tailings from the plant. In addition, variability in the feed rate was included in order to simulate the performance of the circuit. Empirical and phenomenological mathematical models, of each unit operation of the processing circuit, were calibrated in the simulator. The representativeness of the tool was proven by the confrontation of the results obtained against the data from the laboratory. The variables of the models were changed during the dynamic simulation to reproduce the usual control done by the operators. To provide comparison data another scenario was simulated with advanced process control. This was possible due to the fact that the simulator has a data manager performed by an artificial intelligence that allows configuring process control strategies, such as an expert system. After the analysis of simulation results, it was possible to estimate the improvement obtained with the implementation of an expert system through evidence of increased Nickel metallurgical recovery. There was also reduction of the variability of product quality. The above mentioned results shows that techniques for advanced process control are among the most effective methods in cost and time to improve plant performance.