A Reference Process Model for Machine Learning Aided Production Quality Management

Alexander Gerling, Ulf Schreier, Andreas Hess, Alaa Saleh, Holger Ziekow, Djaffar Abdeslam

2020

Abstract

The importance of machine learning (ML) methods has been increasing in recent years. This is also the reason why ML processes in production are becoming more and more widespread. Our objective is to develop a ML aided approach supporting production quality. To get an overview, we describe the manufacturing domain and use a visualization to explain the typical structure of a production line. Within this section we illustrate and explain the as-is process to eliminate an error in the production line. Afterwards, we describe a careful analysis of requirements and challenges for a ML system in this context. A basic idea of the system is the definition of product testing meta data and the exploitation of this knowledge inside the ML system. Also, we define a to-be process with ML system assistance for checking production errors. For this purpose, we describe the associated actors and tasks as well.

Paper Citation

in Harvard Style

Gerling A., Schreier U., Hess A., Saleh A., Ziekow H. and Abdeslam D. (2020). A Reference Process Model for Machine Learning Aided Production Quality Management.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-423-7, pages 515-523. DOI: 10.5220/0009379705150523

in Bibtex Style

@conference{iceis20,
author={Alexander Gerling and Ulf Schreier and Andreas Hess and Alaa Saleh and Holger Ziekow and Djaffar Abdeslam},
title={A Reference Process Model for Machine Learning Aided Production Quality Management},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2020},
pages={515-523},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009379705150523},
isbn={978-989-758-423-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Reference Process Model for Machine Learning Aided Production Quality Management
SN - 978-989-758-423-7
AU - Gerling A.
AU - Schreier U.
AU - Hess A.
AU - Saleh A.
AU - Ziekow H.
AU - Abdeslam D.
PY - 2020
SP - 515
EP - 523
DO - 10.5220/0009379705150523