A multivariate KPI-based method for quality assurance in lithium-ion-battery production

T. Kornas; E. Knak; R. Daub; U. Bührer; C. Lienemann; H. Heimes; A. Kampker; S. Thiede; C. Herrmann

doi:10.1016/j.procir.2019.03.014

A multivariate KPI-based method for quality assurance in lithium-ion-battery production

T. Kornas, E. Knak, R. Daub, U. Bührer, C. Lienemann, H. Heimes, A. Kampker, S. Thiede, C. Herrmann

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

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Abstract

The development of lithium-ion batteries (LIBs) is facing challenges due to the high level of uncertainty in cause-effect-relationships (CERs) in the manufacturing process. This process is characterized as an interlinked chain of input, intermediate and quality properties, which determine the quality of LIBs. In order to reduce the ramp-up time for LIB production plants, an understanding of influencing properties must be established. Existing methods to investigate these properties are usually expert-based or assess individual process steps. Thus, this paper presents a method, which utilizes multivariate process capability indices for the identification of CERs and quality assurance in the field of LIB production. This data-driven approach was applied to and evaluated on the production data of the prototype line for prismatic LIBs at the BMW Group in Munich.

Original language	English
Pages (from-to)	75-80
Journal	Procedia CIRP
Volume	81
DOIs	https://doi.org/10.1016/j.procir.2019.03.014
Publication status	Published - 2019
Externally published	Yes
Event	52nd CIRP Conference on Manufacturing Systems, CIRP CMS 2019 - Ljubljana, Slovenia Duration: 12 Jun 2019 → 14 Jun 2019 Conference number: 52

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10.1016_j.procir.2019.03.014Final published version, 1 MBLicence: CC BY-NC-ND

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title = "A multivariate KPI-based method for quality assurance in lithium-ion-battery production",

abstract = "The development of lithium-ion batteries (LIBs) is facing challenges due to the high level of uncertainty in cause-effect-relationships (CERs) in the manufacturing process. This process is characterized as an interlinked chain of input, intermediate and quality properties, which determine the quality of LIBs. In order to reduce the ramp-up time for LIB production plants, an understanding of influencing properties must be established. Existing methods to investigate these properties are usually expert-based or assess individual process steps. Thus, this paper presents a method, which utilizes multivariate process capability indices for the identification of CERs and quality assurance in the field of LIB production. This data-driven approach was applied to and evaluated on the production data of the prototype line for prismatic LIBs at the BMW Group in Munich.",

author = "T. Kornas and E. Knak and R. Daub and U. B{\"u}hrer and C. Lienemann and H. Heimes and A. Kampker and S. Thiede and C. Herrmann",

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doi = "10.1016/j.procir.2019.03.014",

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AU - Kornas, T.

AU - Knak, E.

AU - Daub, R.

AU - Bührer, U.

AU - Lienemann, C.

AU - Heimes, H.

AU - Kampker, A.

AU - Thiede, S.

AU - Herrmann, C.

N1 - Conference code: 52

PY - 2019

Y1 - 2019

N2 - The development of lithium-ion batteries (LIBs) is facing challenges due to the high level of uncertainty in cause-effect-relationships (CERs) in the manufacturing process. This process is characterized as an interlinked chain of input, intermediate and quality properties, which determine the quality of LIBs. In order to reduce the ramp-up time for LIB production plants, an understanding of influencing properties must be established. Existing methods to investigate these properties are usually expert-based or assess individual process steps. Thus, this paper presents a method, which utilizes multivariate process capability indices for the identification of CERs and quality assurance in the field of LIB production. This data-driven approach was applied to and evaluated on the production data of the prototype line for prismatic LIBs at the BMW Group in Munich.

AB - The development of lithium-ion batteries (LIBs) is facing challenges due to the high level of uncertainty in cause-effect-relationships (CERs) in the manufacturing process. This process is characterized as an interlinked chain of input, intermediate and quality properties, which determine the quality of LIBs. In order to reduce the ramp-up time for LIB production plants, an understanding of influencing properties must be established. Existing methods to investigate these properties are usually expert-based or assess individual process steps. Thus, this paper presents a method, which utilizes multivariate process capability indices for the identification of CERs and quality assurance in the field of LIB production. This data-driven approach was applied to and evaluated on the production data of the prototype line for prismatic LIBs at the BMW Group in Munich.

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DO - 10.1016/j.procir.2019.03.014

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JO - Procedia CIRP

JF - Procedia CIRP

T2 - 52nd CIRP Conference on Manufacturing Systems, CIRP CMS 2019

Y2 - 12 June 2019 through 14 June 2019

ER -

A multivariate KPI-based method for quality assurance in lithium-ion-battery production

Abstract

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