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Authors: Richard Nordsieck 1 ; Michael Heider 2 ; Andreas Angerer 1 and Jörg Hähner 2

Affiliations: 1 XITASO GmbH IT & Software Solutions, Augsburg and Germany ; 2 Organic Computing Group, University of Augsburg, Augsburg and Germany

Keyword(s): Additive Manufacturing, Transfer Learning, Domain Adaption, Machine Learning, Knowledge Representation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Evolutionary Computation and Control ; Industrial Engineering ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge-Based Systems Applications ; Machine Learning in Control Applications ; Optimization Algorithms ; Resources and Knowledge Management in Industry

Abstract: Commissioning of machines takes up a considerable share of time and money of the total cost of developing a machine. Our project aims at developing an approach to decrease the time needed to commission machines by automating parameter optimisation with the help of formalised expert knowledge. The approach will be developed on the Fused Deposition Modelling (FDM) process, which is an additive manufacturing technique. We pay particular attention to keeping the approach sufficiently abstract to be applied to machines from other domains to benefit its industrial application.

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Paper citation in several formats:
Nordsieck, R.; Heider, M.; Angerer, A. and Hähner, J. (2019). Towards Automated Parameter Optimisation of Machinery by Persisting Expert Knowledge. In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-380-3; ISSN 2184-2809, SciTePress, pages 406-413. DOI: 10.5220/0007953204060413

@conference{icinco19,
author={Richard Nordsieck. and Michael Heider. and Andreas Angerer. and Jörg Hähner.},
title={Towards Automated Parameter Optimisation of Machinery by Persisting Expert Knowledge},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2019},
pages={406-413},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007953204060413},
isbn={978-989-758-380-3},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Towards Automated Parameter Optimisation of Machinery by Persisting Expert Knowledge
SN - 978-989-758-380-3
IS - 2184-2809
AU - Nordsieck, R.
AU - Heider, M.
AU - Angerer, A.
AU - Hähner, J.
PY - 2019
SP - 406
EP - 413
DO - 10.5220/0007953204060413
PB - SciTePress

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