Making implicit knowledge explicit – Acquisition of plant staff’s mental models as a basis for developing a decision support system

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12 Scopus citations

Abstract

Monitoring of industrial production plants is a complex task, which requires a hight level of knowledge about the interrelations in the production process in many cases. This knowledge on the one hand, is available as handbooks, process models or process data. On the other hand, the plant’s staff has implicit knowledge in the form of mental models. Experienced process engineers and operators have improved these mental models over years of working with the process. In this paper, a procedure is described, of how implicit knowledge can be made explicit by the acquisition of plant’s staff mental models. The aim is to build a cause-effect model for different quality parameters, which can be integrated into a decision support system (DSS), which helps the operator in decision-making.

Original languageEnglish
Title of host publicationHCI International 2017 - Posters Extended Abstracts - 19th International Conference, HCI International 2017, Proceedings
EditorsConstantine Stephanidis
PublisherSpringer Verlag
Pages358-365
Number of pages8
ISBN (Print)9783319587493
DOIs
StatePublished - 2017
Event19th International Conference on Human-Computer Interaction, HCI International 2017 - Vancouver, Canada
Duration: 9 Jul 201714 Jul 2017

Publication series

NameCommunications in Computer and Information Science
Volume713
ISSN (Print)1865-0929

Conference

Conference19th International Conference on Human-Computer Interaction, HCI International 2017
Country/TerritoryCanada
CityVancouver
Period9/07/1714/07/17

Keywords

  • Decision making
  • Knowledge acquisition
  • Mental model
  • Plant manufacturing

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