Predictive Maintenance and Performance Monitoring Using Simultaneous Data Reconciliation and Parameter Estimation

After the feedstock supply and the energy consumption, process maintenances represent the largest voice in operative costs for refineries and petrochemical plants. Moreover, to further reduce profit margins, failure maintenances due to accidents or malfunctions can occur without notice, by influencing the overall production and the operational planning. Performance monitoring is a suitable tool for predictive maintenance in chemical process. In this paper, we integrate rigorous simulation model, data reconciliation and parameter estimation to monitor process equipments and determine key performance indicator (KPI) of them for predictive maintenance. The applied method here has been implemented on two case studies

Keywords:

Performance Monitoring , Predictive Maintenance , Data Validation , Parameter Estimation , Measurement