Tracking and tracing for data mining application in the lithium-ion battery production

Jacob Wessel; Artem Turetskyy; Olaf Wojahn; Christoph Herrmann; Sebastian Thiede

doi:10.1016/j.procir.2020.03.071

Tracking and tracing for data mining application in the lithium-ion battery production

Jacob Wessel^*, Artem Turetskyy, Olaf Wojahn, Christoph Herrmann, Sebastian Thiede

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Academic › peer-review

29 Citations (Scopus)

107 Downloads (Pure)

Abstract

The production of Lithium-Ion Battery (LIB) cells is characterized by the interlinking of different production processes with a manifold of intermediate products. To be able to ensure high quality and enable a traceability of different production and product characteristics (e.g. energy consumption, material), a tracking and tracing concept is required. In this paper, a practical tracking and tracing concept throughout the production of LIB cells, enabling inline data-driven applications, is introduced. As a part of this concept an intelligent tracking and tracing platform is shown, which allows the generation of a pre-clustered data sets to facilitate future data-driven applications.

Original language	English
Pages (from-to)	162-167
Number of pages	6
Journal	Procedia CIRP
Volume	93
DOIs	https://doi.org/10.1016/j.procir.2020.03.071
Publication status	Published - 22 Sept 2020
Externally published	Yes
Event	53rd CIRP Conference on Manufacturing Systems, CIRP CMS 2020 - Virtual Conference, Chicago, United States Duration: 1 Jul 2020 → 3 Jul 2020 Conference number: 53

Keywords

Data allocation
Data mining
Lithium-ion battery cells
Manufacturing
Traceability
Traceability system
Tracking and tracing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016_j.procir.2020.03.071Final published version, 881 KBLicence: CC BY-NC-ND

Cite this

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title = "Tracking and tracing for data mining application in the lithium-ion battery production",

abstract = "The production of Lithium-Ion Battery (LIB) cells is characterized by the interlinking of different production processes with a manifold of intermediate products. To be able to ensure high quality and enable a traceability of different production and product characteristics (e.g. energy consumption, material), a tracking and tracing concept is required. In this paper, a practical tracking and tracing concept throughout the production of LIB cells, enabling inline data-driven applications, is introduced. As a part of this concept an intelligent tracking and tracing platform is shown, which allows the generation of a pre-clustered data sets to facilitate future data-driven applications.",

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author = "Jacob Wessel and Artem Turetskyy and Olaf Wojahn and Christoph Herrmann and Sebastian Thiede",

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language = "English",

volume = "93",

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journal = "Procedia CIRP",

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AU - Wessel, Jacob

AU - Turetskyy, Artem

AU - Wojahn, Olaf

AU - Herrmann, Christoph

AU - Thiede, Sebastian

N1 - Conference code: 53

PY - 2020/9/22

Y1 - 2020/9/22

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AB - The production of Lithium-Ion Battery (LIB) cells is characterized by the interlinking of different production processes with a manifold of intermediate products. To be able to ensure high quality and enable a traceability of different production and product characteristics (e.g. energy consumption, material), a tracking and tracing concept is required. In this paper, a practical tracking and tracing concept throughout the production of LIB cells, enabling inline data-driven applications, is introduced. As a part of this concept an intelligent tracking and tracing platform is shown, which allows the generation of a pre-clustered data sets to facilitate future data-driven applications.

KW - Data allocation

KW - Data mining

KW - Lithium-ion battery cells

KW - Manufacturing

KW - Traceability

KW - Traceability system

KW - Tracking and tracing

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DO - 10.1016/j.procir.2020.03.071

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VL - 93

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T2 - 53rd CIRP Conference on Manufacturing Systems, CIRP CMS 2020

Y2 - 1 July 2020 through 3 July 2020

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Tracking and tracing for data mining application in the lithium-ion battery production

Abstract

Keywords

UN SDGs

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