Title data
Kaymakci, Can ; Wenninger, Simon ; Sauer, Alexander:
A Holistic Framework for AI Systems in Industrial Applications.
In:
Proceedings of the 16th International Conference on Wirtschaftsinformatik (WI). -
Duisburg, Germany
,
2021
Project information
Project title: |
Project's official title Project's id Projektgruppe WI Digital Finance No information Projektgruppe WI Künstliche Intelligenz No information |
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Abstract in another language
Although several promising use cases for artificial intelligence (AI) for manufacturing companies have been identified, these are not yet widely used. Existing literature covers a variety of frameworks, methods and processes related to AI systems. However, the application of AI systems in manufacturing companies lacks a uniform understanding of components and functionalities as well as a structured process that supports developers and project managers in planning, implementing, and optimizing AI systems. To close this gap, we develop a generic conceptual model of an AI system for the application in manufacturing systems and a four-phase model to guide developers and project managers through the realization of AI systems.
Further data
Item Type: | Article in a book |
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Refereed: | Yes |
Keywords: | Manufacturing AI System; Intelligent Agents; Machine Learning |
Institutions of the University: | Faculties > Faculty of Law, Business and Economics > Department of Business Administration Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management Faculties Faculties > Faculty of Law, Business and Economics |
Result of work at the UBT: | No |
DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics |
Date Deposited: | 17 Dec 2020 08:28 |
Last Modified: | 27 Jun 2022 06:03 |
URI: | https://eref.uni-bayreuth.de/id/eprint/61190 |