(X)AI-SPOT: an (X)AI-Supported Production Process Optimization Tool

Inti Gabriel Mendoza Estrada, Vedran Sabol, Hanna Müller, Johannes Georg Hoffer

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

Abstract

We demonstrate (X)AI-SPOT - (X)AI-Supported Process Optimization Tool - that aims to encourage, facilitate, and enhance AI usage for process engineering and optimization in the production industry. Furthermore, (X)AI-SPOT seeks not to become a one-size-fits-all approach but a framework where each user archetype (Shop Floor Worker, Field Expert, and AI Expert) can receive tailored XAI functionality suited to their unique requirements. Currently, (X)AI-SPOT handles the Shop Floor Worker user archetype, with initial support for the Field Expert. We also describe our tool's architecture w.r.t. extendibility and support of different user archetypes; we share our findings from an expert user interview and conclude with a discussion of design decisions and future work. Our application is available at http://exait.know-center.at/mv-ui.

Original languageEnglish
Title of host publicationCompanion Proceedings of 29th International Conference on Intelligent User Interfaces, IUI 2024
PublisherAssociation of Computing Machinery
Pages66-69
Number of pages4
ISBN (Electronic)9798400705090
DOIs
Publication statusPublished - 18 Mar 2024
Event29th International Conference on Intelligent User Interfaces, IUI 2024 - Greenville, United States
Duration: 18 Mar 202421 Mar 2024

Publication series

NameACM International Conference Proceeding Series

Conference

Conference29th International Conference on Intelligent User Interfaces, IUI 2024
Country/TerritoryUnited States
CityGreenville
Period18/03/2421/03/24

Keywords

  • eXplainable AI
  • knowledge visualization
  • metamodels
  • process optimization

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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