Study On Process Simulation For The Ethylene Plant And Its Application Based On The Concept Of Digital Factory

Ethylene producing and separation unit is the typical large-scale continuous chemical production plant; its process program is complex and frequent malfunction. How to realize the strict on-line dynamic simulation of the process, obtain the simulation data close to the produce reality, then guide for production effectively, it has great realistic meaning. Research subject of this paper is proposed based on the background above, focusing on the following questions:1 Digital factory of data-centric for ethylene plant can realize Manufacturing Execution System (MES). Safe and optimized production can be achieved by Digital factory based on strict steady-state and dynamic models using Proprietary software SIMACS.2 The key issue for establishing a data-centric digital factory is how to transfer data from various types of distributed control system (DCS) or Laboratory Information Management System (LIMS) to the real-time database. The DCS and LIMS data collection method for conventional ethylene plant is lagging, unstable, poor-compatible. To solve the problems, MATRICON OPC(OLE for Process Control) technology is presented here to improve the conventional OPC technology for real-time data acquisition. It has so many excellent characteristics such as large quantity of data transmission, high speed, high stability, data safety that will meet the demands of upper application program completely.3 The key issue for establishing a digital factory based on strict Steady-state and dynamic model is how to combine the two models. Comparing the real-time data from actual plants and data from dynamic models, adapting and correcting the model parameters in real-time, ensure the accuracy of dynamic model, so that the strict Steady-state and dynamic models can reflect the actual situation of the factory better. Chemical process on-line dynamic simulation technology is presented here. It is combined by Steady-state and dynamic models based on Proprietary software SIMACS.4 We studied the establishment of intelligent digital factories based on digital factories which is based on strict steady state and dynamic models. Using data mining method, we can define the intelligent fault diagnosis knowledge representation and C4.5 decision tree. The method has been used in ethylene plant. Good economic results were achieved.