A simulation framework for industrial wireless networks and process control systems


Factory and process automation systems are increasingly employing information and communications technologies to facilitate data sharing and analysis in integrated control operations. Wireless connections provide flexible access to a variety of field instruments and reduce network installation and maintenance costs. This serves as an incentive for the adoption of industrial wireless networks based on standards such as the WirelessHART and ISA100.11a in factory control systems. However, process control systems vary greatly and have diverse wireless networking requirements in different applications. These requirements include deterministic transmissions in the shared wireless bandwidth, low-cost operation, long-term durability, and high reliability in the harsh radio propagation environment. It is an open question whether a generic wireless technology would meet the requirements of industrial process control. In this paper, we propose a novel simulation framework for performance evaluation of wireless networks in factory and process automation systems. We select a typical process control plant model, specifically the Tennessee Eastman Challenge (TE) Model, and define the interfaces between the process simulator and the wireless network simulator. We develop a model of the protocol stack of the WirelessHART specification in the OMNET++ simulation engine as a typical industrial wireless network. We present simulation results that validate the prospect of using WirelessHART in the TE plant, and we evaluate the impact of various wireless network configurations on the plant operation. Given its modular design, the proposed simulation framework can be easily used to evaluate the performance of other industrial wireless networks in conjunction with a variety of process control systems.

DOI: 10.1109/WFCS.2016.7496495

Cite this paper

@inproceedings{Liu2016ASF, title={A simulation framework for industrial wireless networks and process control systems}, author={Yongkang Liu and Richard Candell and Kang Ro Lee and Nader Moayeri}, booktitle={WFCS}, year={2016} }