From stirring to mixing: artificial intelligence in the process industry

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

Contributors

Abstract

The introduction of AI methods in production or production-related environments meets with resistance from operators due to their lack of relevant experience and their responsibility for plant safety. To overcome these inhibitions one requires prototypical implementations, which offer considerable benefits, meet the highest requirements for reliability, are accepted by the operating personnel, and get support from those in charge. As a result, AI technologies must be embedded into the complex IT/OT infrastructure of the companies. Traceability, maintainability and longevity must also be guaranteed. As a first step towards this, we present a concept of the demonstrator and its first results, which should make AI comprehensible by visualizing challenges and exploring possibilities in the process industry.

Details

Original languageEnglish
Title of host publication2020 25TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA)
PublisherWiley-IEEE Press
Pages967-974
Number of pages8
Publication statusPublished - 2020
Peer-reviewedYes

Conference

Title2020 25th IEEE International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA 2020
Conference number25
Duration8 - 11 September 2020
Website
Degree of recognitionInternational event
LocationTU Wien & online
CityVienna
CountryAustria

External IDs

Scopus 85093364861
ORCID /0000-0001-5165-4459/work/142248235

Keywords

Keywords

  • Modular plant, Bioreactor, AI-based surrogate models, CFD-simulation, object recognition, AR-application, BUBBLE COALESCENCE, Modular plant, Bioreactor, Al-based surrogate models, CFD-simulation, object recognition, AR-application