Towards cloud-based Control-as-a-Service for modular Process Plants

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review



BACKGROUND: Computational and data-intensive technologies such as model predictive control and artificial intelligence have the potential to increase process yields in the process industry. In modular plant designs, the flexible and difficult-to-predict use of a particular module presents the challenge of providing the right amount of data, computing power, and storage capacity to use these technologies in each module.OBJECTIVE: Simplifying the deployment and reconfiguration of compute-intensive applications for modular plants.METHODS: Reviewing the current state of the art and combining the modular plant concept with a cloud-based Control-as-a-Service (CaaS) approach.RESULTS: A cloud-based, containerized CaaS concept that supports the deployment compute- and data-intensive methods for modular plants. The complementing communication stack consisting of standards such as APL, TSN and OPC UA FX.CONCLUSION: The proposed architecture simplifies IT/OT integration, eases the deployment of compute-intensive technologies, and allows for GMP compliant pre-qualification of software modules. However, the limiting factors like plant safety, conformity to regulations and widespread architecture adoption are not covered in detail and will be subject of future research.


Original languageEnglish
Title of host publication2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
Place of PublicationSinaia, Romania
ISBN (electronic)9798350339918
Publication statusPublished - 12 Sept 2023


Title2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA2023
Conference number28
Duration12 - 15 September 2023
Degree of recognitionInternational event
LocationInternational Centre for Conferences – CASINO Sinaia

External IDs

ORCID /0000-0003-3954-7786/work/144670589
ORCID /0000-0001-5165-4459/work/144671157
ORCID /0000-0003-3368-4130/work/144671366
Scopus 85175467770
Mendeley 9b3a7dd4-efb8-3e9f-b3d7-577652392a17


Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Subject groups, research areas, subject areas according to Destatis


  • cloud, containerization, modular plant, process control systems