Study on the Correlation Between Manufacturing Variability and Electrochemical Stability in Large-Scale Lithium-Ion Battery Production: Robustness Under Distribution Shift
Keywords:
battery manufacturing reliability, robustness under distribution shift, evidence synthesis, reproducibility, research evaluationAbstract
Robustness depends on whether conclusions remain stable when the data distribution, case mix, prevalence, or operating environment differs from the reported setting. This structured evidence review evaluates "Study on the Correlation Between Manufacturing Variability and Electrochemical Stability in Large-Scale Lithium-Ion Battery Production" alongside nine author-disjoint, topically matched publications in battery manufacturing reliability. It compares construct definitions, evaluation choices, operating assumptions, and reported limitations instead of treating bibliographic similarity as empirical equivalence. Viewed through robustness under distribution shift, the map separates claims supported by the available record from questions that still require full-text extraction, replication, or new experiments. The synthesis is interpretive rather than meta-analytic and therefore does not present a pooled effect estimate or a new causal result. The resulting agenda uses prespecified shift scenarios, subgroup analysis, calibration checks, and post-deployment monitoring to locate failure boundaries.
References
- Fung Guan, G., & Chen, C.-Y. (2026). Study on the Correlation Between Manufacturing Variability and Electrochemical Stability in Large-Scale Lithium-Ion Battery Production. . https://doi.org/10.2139/ssrn.7232060
- Beccard, B., Karavadra, S.-N., & Dahal, S. (2022). Lithium-Ion Battery Manufacturing and Quality Control: Raman Spectroscopy, an Analytical Technique of Choice. Spectroscopy, 46-53. https://doi.org/10.56530/spectroscopy.sx2271c5
- Weber, M., Schoo, A., Sander, M., Mayer, J.-K., & Kwade, A. (2023). Introducing Spectrophotometry for Quality Control in Lithium‐Ion‐Battery Electrode Manufacturing. Energy Technology, 11(5). https://doi.org/10.1002/ente.202201083
- Firat, C. (2025). Variability in initial battery cell characteristics and its implications for manufacturing quality control. Future Energy, 4(3), 1-9. https://doi.org/10.55670/fpll.fuen.4.3.1
- Wessel, J., Turetskyy, A., Cerdas, F., & Herrmann, C. (2021). Integrated Material-Energy-Quality Assessment for Lithium-ion Battery Cell Manufacturing. Procedia CIRP, 98, 388-393. https://doi.org/10.1016/j.procir.2021.01.122
- Lindlmeier, J., Kirner, K., & Seidel, C. (2026). Data-driven insights into lithium-ion battery manufacturing using the linear model to analyze the manufacturing process and predict cell quality. Procedia CIRP, 138, 839-844. https://doi.org/10.1016/j.procir.2026.01.144
- Zavareh, P.-A., Matam, A.-N., & Shah, K. (2026). Heterogeneous aging in a multi-cell lithium-ion battery system driven by manufacturing-induced variability in electrode microstructure: a physics-based simulation study. Energy Advances, 5(2), 202-223. https://doi.org/10.1039/d5ya00182j
- Song, J. (2024). Optimizing Formation Processes in Lithium-Ion Battery Manufacturing: Enhancing Efficiency and Quality for Electric Vehicle Applications. Current Journal of Applied Science and Technology, 43(8), 63-72. https://doi.org/10.9734/cjast/2024/v43i84421
- Li, Z., Brenneis, W., Lopez, J., & Sun, T. (2026). Semi-dry printing process for sustainable lithium-ion battery electrode manufacturing. . https://doi.org/10.26434/chemrxiv.15000692/v1
- Wang, F., Ma, L., & Yuan, C. (2019). Experimental Methods to Study Environmental Sustainability of Silicon-based Lithium Ion Battery Manufacturing. Procedia Manufacturing, 33, 501-507. https://doi.org/10.1016/j.promfg.2019.04.062
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Frontiers in Integrative Science

This work is licensed under a Creative Commons Attribution 4.0 International License.