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Authors: Alexander Gerling 1 ; 2 ; 3 ; Christian Seiffer 1 ; Holger Ziekow 1 ; Ulf Schreier 1 ; Andreas Hess 1 and Djaffar Ould Abdeslam 2 ; 3

Affiliations: 1 Business Information Systems, Furtwangen University of Applied Science, 78120 Furtwangen, Germany ; 2 IRIMAS Laboratory, Université de Haute-Alsace, 68100 Mulhouse, France ; 3 Université de Strasbourg, 67081 Strasbourg, France

Keyword(s): Machine Learning, Explainable ML, Manufacturing, Domain Expert Interviews.

Abstract: Machine Learning (ML) is increasingly used in the manufacturing domain to identify the root cause of product errors. A product error can be difficult to identify and most ML models are not easy to understand. Therefore, we investigated visualization techniques for use in manufacturing. We conducted several interviews with quality engineers and a group of students to determine the usefulness of 15 different visualizations. These are mostly state-of-the-art visualizations or adjusted visualizations for our use case. The objective is to prevent misinterpretations of results and to help making decisions more quickly. The most popular visualizations were the Surrogate Decision Tree Model and the Scatter Plot because they show simple illustrations that are easy to understand. We also discuss eight combinations of visualizations to better identify the root cause of an error.

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Paper citation in several formats:
Gerling, A.; Seiffer, C.; Ziekow, H.; Schreier, U.; Hess, A. and Abdeslam, D. (2021). Evaluation of Visualization Concepts for Explainable Machine Learning Methods in the Context of Manufacturing. In Proceedings of the 5th International Conference on Computer-Human Interaction Research and Applications - CHIRA; ISBN 978-989-758-538-8; ISSN 2184-3244, SciTePress, pages 189-201. DOI: 10.5220/0010688900003060

@conference{chira21,
author={Alexander Gerling. and Christian Seiffer. and Holger Ziekow. and Ulf Schreier. and Andreas Hess. and Djaffar Ould Abdeslam.},
title={Evaluation of Visualization Concepts for Explainable Machine Learning Methods in the Context of Manufacturing},
booktitle={Proceedings of the 5th International Conference on Computer-Human Interaction Research and Applications - CHIRA},
year={2021},
pages={189-201},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010688900003060},
isbn={978-989-758-538-8},
issn={2184-3244},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Computer-Human Interaction Research and Applications - CHIRA
TI - Evaluation of Visualization Concepts for Explainable Machine Learning Methods in the Context of Manufacturing
SN - 978-989-758-538-8
IS - 2184-3244
AU - Gerling, A.
AU - Seiffer, C.
AU - Ziekow, H.
AU - Schreier, U.
AU - Hess, A.
AU - Abdeslam, D.
PY - 2021
SP - 189
EP - 201
DO - 10.5220/0010688900003060
PB - SciTePress

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