Towards a Smart Electronics Production Using Machine Learning Techniques

Seidel R, Mayr A, Schäfer F, Kißkalt D, Franke J (2019)

Publication Type: Conference contribution

Publication year: 2019

Edited Volumes: International Spring Seminar on Electronics Technology, ISSE 2019 -- 2019 42th International Spring Seminar

Pages Range: 1--6

Conference Proceedings Title: 2019 42nd International Spring Seminar on Electronics Technology (ISSE)

Event location: Wroclaw

URI: https://ieeexplore.ieee.org/document/8810176

DOI: 10.1109/ISSE.2019.8810176

Abstract

High quality and low costs are main drivers in electronics production. Regardless of the application, the trend towards batch size 1 heavily challenges current production systems. With higher data availability, the application of machine learning (ML) has great potential for the future of electronics production. Therefore, this paper gives an overview about exemplary investigations of ML techniques in the assembly of surface mount devices (SMD) and shows the need for a systematic proceeding when searching for profitable ML use cases. In doing so, a process-oriented methodology for the identification of ML use cases is derived, paving the way towards a smart electronics production.

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APA:

Seidel, R., Mayr, A., Schäfer, F., Kißkalt, D., & Franke, J. (2019). Towards a Smart Electronics Production Using Machine Learning Techniques. In 2019 42nd International Spring Seminar on Electronics Technology (ISSE) (pp. 1--6). Wroclaw, PL.

MLA:

Seidel, Reinhardt, et al. "Towards a Smart Electronics Production Using Machine Learning Techniques." Proceedings of the 42nd International Spring Seminar on Electronics Technology (ISSE), Wroclaw 2019. 1--6.

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