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

James Kabugo, Sirkka-Liisa Jämsä-Jounela, Robert Schiemann, Christian Binder

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

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 temperature. 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.
Original languageEnglish
Title of host publication4th Conference on Control and Fault Tolerant Systems (SysTol)
PublisherIEEE
Pages264-269
Number of pages6
ISBN (Electronic)978-1-7281-0380-8
ISBN (Print)978-1-7281-0381-5
DOIs
Publication statusPublished - 14 Oct 2019
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Control and Fault-Tolerant Systems - Casabalanca, Morocco
Duration: 18 Sep 201920 Sep 2019
Conference number: 4
http://www.systol.org/systol19/

Publication series

NameConference on Control and Fault Tolerant Systems (SysTol)
PublisherIEEE
ISSN (Print)2162-1195
ISSN (Electronic)2162-1209

Conference

ConferenceInternational Conference on Control and Fault-Tolerant Systems
Abbreviated titleSysTol
CountryMorocco
CityCasabalanca
Period18/09/201920/09/2019
Internet address

Keywords

  • Industrial internet of things , machine learning , waste-to-energy , soft sensor
  • machine learning
  • waste-to-energy
  • soft sensor
  • Cloud computing
  • Data analysis
  • Temperature sensors
  • Data models
  • Automation

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  • Cite this

    Kabugo, J., Jämsä-Jounela, S-L., Schiemann, R., & Binder, C. (2019). Process Monitoring Platform based on Industry 4.0 tools: a waste-to-energy plant case study. In 4th Conference on Control and Fault Tolerant Systems (SysTol) (pp. 264-269). (Conference on Control and Fault Tolerant Systems (SysTol)). IEEE. https://doi.org/10.1109/SYSTOL.2019.8864766