Process Monitoring Platform based on Industry 4.0 tools: a waste-to-energy plant case study

James Clovis Kabugo, Sirkka-Liisa Jamsa-Jounela, Robert Schiemann, Christian Binder
2019 2019 4th Conference on Control and Fault Tolerant Systems (SysTol)  
This work presents a process data analytics platform built around the concept of industry 4.0. The platform utilizes the state-of-the-art industry internet of things (IIoT) platforms, machine learning (ML) algorithms and big-data software tools. The industrial applicability of the platform was demonstrated by the development of soft sensors for use in a waste-to-energy (WTE) plant. In the case study, the work studied data-driven soft sensors to predict syngas heating value and hot flue gas
more » ... rature. From data-driven models, the neural network based nonlinear autoregressive with external input (NARX) model demonstrated better performance in prediction of both syngas heating value and flue gas temperature in a WTE process.
doi:10.1109/systol.2019.8864766 dblp:conf/systol/KabugoJSB19 fatcat:ddhvawl5mzfmxmnuj7ljdvum4q