Sicong Deng , Jonas Wieskamp , Henrik Born , Heiner Hans Heimes , Achim Kampker
{"title":"Modeling flexible configuration of cell finishing for future battery production research","authors":"Sicong Deng , Jonas Wieskamp , Henrik Born , Heiner Hans Heimes , Achim Kampker","doi":"10.1016/j.rcim.2025.103119","DOIUrl":null,"url":null,"abstract":"<div><div>Today, the increasing demand for battery cells requires efficient large-scale production. At the same time, cell design continues to improve regarding various performance metrics causing product feature changes, which in turn affect the process chain, equipment and process parameter design in production. In cell finishing – the final cell production section – both external cell features, related to the system components, and internal cell features, related to process protocol, are directly affected. However, the interrelations between the core domains – product, process, parameters and equipment – are hardly assessed in the current cell finishing planning and thus no systematic approach to configuration design has been established. This paper focuses on this research need and presents an approach through configuration modeling based on Modularization and Knowledge-Based Design and uses real data from factory planning. From the analyzed raw data, a structured database of product, process, parameters, equipment and their interrelations are derived. For this modeling approach, the paper first explains the conceptual framework. Then, it introduces domains and sub-domains of the database and their formalization for modeling. Subsequently, the architecture of a Two-Stage Configuration Model is explained for flexible configurations (first stage) and virtual modeling (second stage). Finally, the modeling approach is implemented for a real case of prismatic cell finishing. It demonstrates how various configurations can be systematically generated and visualized based on design requirements to advance design optimizations in cell finishing for research purposes and industrial application.</div></div>","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"98 ","pages":"Article 103119"},"PeriodicalIF":11.4000,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736584525001735","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Today, the increasing demand for battery cells requires efficient large-scale production. At the same time, cell design continues to improve regarding various performance metrics causing product feature changes, which in turn affect the process chain, equipment and process parameter design in production. In cell finishing – the final cell production section – both external cell features, related to the system components, and internal cell features, related to process protocol, are directly affected. However, the interrelations between the core domains – product, process, parameters and equipment – are hardly assessed in the current cell finishing planning and thus no systematic approach to configuration design has been established. This paper focuses on this research need and presents an approach through configuration modeling based on Modularization and Knowledge-Based Design and uses real data from factory planning. From the analyzed raw data, a structured database of product, process, parameters, equipment and their interrelations are derived. For this modeling approach, the paper first explains the conceptual framework. Then, it introduces domains and sub-domains of the database and their formalization for modeling. Subsequently, the architecture of a Two-Stage Configuration Model is explained for flexible configurations (first stage) and virtual modeling (second stage). Finally, the modeling approach is implemented for a real case of prismatic cell finishing. It demonstrates how various configurations can be systematically generated and visualized based on design requirements to advance design optimizations in cell finishing for research purposes and industrial application.
期刊介绍:
The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.