Multi-Criteria Optimization in the Production of Lithium-Ion Batteries

Thomas Kornas; Dominik Wittmann; Rüdiger Daub; Oliver Meyer; Claus Weihs; Sebastian Thiede; Christoph Herrmann

doi:10.1016/j.promfg.2020.02.113

Multi-Criteria Optimization in the Production of Lithium-Ion Batteries

Thomas Kornas, Dominik Wittmann, Rüdiger Daub, Oliver Meyer, Claus Weihs, Sebastian Thiede, Christoph Herrmann

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

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Abstract

Lithium-ion-batteries (LIBs) play a key role in determining the environmental impacts of future mobility technologies. In particular, the production of LIBs has a strong environmental impact as it is characterized by high scrap rates. In addition to existing expert-based approaches for the identification of quality drivers in production, a trend towards data-driven methods is discernible. Nevertheless, most approaches show shortcomings in the involvement of multi-criteria optimization. Therefore, this paper uses desirability functions to jointly optimize several quality parameters. Validation was conducted based on the data of an assembly line for prismatic LIBs.

Original language	English
Pages (from-to)	720-727
Number of pages	8
Journal	Procedia manufacturing
Volume	43
DOIs	https://doi.org/10.1016/j.promfg.2020.02.113
Publication status	Published - 2020
Externally published	Yes
Event	17th Global Conference on Sustainable Manufacturing, GCSM 2019 - Tongji University, Shanghai, China Duration: 9 Oct 2019 → 11 Oct 2019 Conference number: 17

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10.1016_j.promfg.2020.02.113Final published version, 799 KBLicence: CC BY-NC-ND

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@article{6d3ea48499234684b053a947ce89a64e,

title = "Multi-Criteria Optimization in the Production of Lithium-Ion Batteries",

abstract = "Lithium-ion-batteries (LIBs) play a key role in determining the environmental impacts of future mobility technologies. In particular, the production of LIBs has a strong environmental impact as it is characterized by high scrap rates. In addition to existing expert-based approaches for the identification of quality drivers in production, a trend towards data-driven methods is discernible. Nevertheless, most approaches show shortcomings in the involvement of multi-criteria optimization. Therefore, this paper uses desirability functions to jointly optimize several quality parameters. Validation was conducted based on the data of an assembly line for prismatic LIBs.",

author = "Thomas Kornas and Dominik Wittmann and R{\"u}diger Daub and Oliver Meyer and Claus Weihs and Sebastian Thiede and Christoph Herrmann",

year = "2020",

doi = "10.1016/j.promfg.2020.02.113",

language = "English",

volume = "43",

pages = "720--727",

journal = "Procedia manufacturing",

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note = "17th Global Conference on Sustainable Manufacturing, GCSM 2019, GCSM 2019 ; Conference date: 09-10-2019 Through 11-10-2019",

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TY - JOUR

T1 - Multi-Criteria Optimization in the Production of Lithium-Ion Batteries

AU - Kornas, Thomas

AU - Wittmann, Dominik

AU - Daub, Rüdiger

AU - Meyer, Oliver

AU - Weihs, Claus

AU - Thiede, Sebastian

AU - Herrmann, Christoph

N1 - Conference code: 17

PY - 2020

Y1 - 2020

N2 - Lithium-ion-batteries (LIBs) play a key role in determining the environmental impacts of future mobility technologies. In particular, the production of LIBs has a strong environmental impact as it is characterized by high scrap rates. In addition to existing expert-based approaches for the identification of quality drivers in production, a trend towards data-driven methods is discernible. Nevertheless, most approaches show shortcomings in the involvement of multi-criteria optimization. Therefore, this paper uses desirability functions to jointly optimize several quality parameters. Validation was conducted based on the data of an assembly line for prismatic LIBs.

AB - Lithium-ion-batteries (LIBs) play a key role in determining the environmental impacts of future mobility technologies. In particular, the production of LIBs has a strong environmental impact as it is characterized by high scrap rates. In addition to existing expert-based approaches for the identification of quality drivers in production, a trend towards data-driven methods is discernible. Nevertheless, most approaches show shortcomings in the involvement of multi-criteria optimization. Therefore, this paper uses desirability functions to jointly optimize several quality parameters. Validation was conducted based on the data of an assembly line for prismatic LIBs.

U2 - 10.1016/j.promfg.2020.02.113

DO - 10.1016/j.promfg.2020.02.113

M3 - Conference article

SN - 2351-9789

VL - 43

SP - 720

EP - 727

JO - Procedia manufacturing

JF - Procedia manufacturing

T2 - 17th Global Conference on Sustainable Manufacturing, GCSM 2019

Y2 - 9 October 2019 through 11 October 2019

ER -

Multi-Criteria Optimization in the Production of Lithium-Ion Batteries

Abstract

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