Challenges in Geometry Assurance of Megacasting in the Automotive Industry

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computing and Information Science in Engineering Pub Date : 2023-04-05 DOI:10.1115/1.4062269
Kristina Wärmefjord, Josefin Hansen, R. Söderberg
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引用次数: 1

Abstract

Megacasting is a new concept in the automotive industry. A large number of sheet metal parts will be replaced with one large aluminum casting, i.e. a megacasting. This helps to reduce weight, opens up for larger design flexibility, allows for a more circular production, and takes away a large number of assembly steps in the production process. However, there are also challenges related to the use of megacastings. This position paper outlines challenges associated with the geometrical quality of the final product. It covers robust design and tolerancing in early product development phases as well as inspection preparation during pre-production and digital twin set-up during full production to ensure the geometrical quality of a product containing a megacasting. Simulations of both part level and assembly level deviation and variation are discussed. The paper outlines a geometry assurance process for products containing megacastings in the automotive industry, and what research challenges that are the most important ones to address in this area. It is concluded that computer-aided tolerancing tools must be able to predict the dimensional effects from joining methods such as flow drill fasteners or self-pierced riveting, to use casting simulation as input, and to handle combinations of solid and surface meshes. Furthermore, there might be a need for adjustments to the joining process based on digital twins to achieve proper quality at a reasonable price. Experiences in using megacastings in the body-in-white are lacking and a fast learning curve is required.
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汽车工业中大型铸件几何保证的挑战
超级铸造是汽车行业的一个新概念。大量的钣金零件将被一个大型铝铸件取代,即一个巨型铸件。这有助于减轻重量,开辟了更大的设计灵活性,允许更循环的生产,并在生产过程中省去了大量的组装步骤。然而,超大型铸件的使用也存在挑战。这份立场文件概述了与最终产品几何质量相关的挑战。它涵盖了早期产品开发阶段的稳健设计和公差,以及生产前的检查准备和全面生产期间的数字孪生设置,以确保包含巨型铸件的产品的几何质量。讨论了零件水平和装配水平偏差和变化的仿真。本文概述了汽车工业中包含大型铸件的产品的几何保证过程,以及该领域最重要的研究挑战。结论是,计算机辅助公差工具必须能够预测连接方法(如流钻紧固件或自穿孔铆接)的尺寸效应,以铸造模拟为输入,并处理实体和表面网格的组合。此外,可能需要调整基于数字孪生的连接过程,以合理的价格获得适当的质量。在白色车身中使用大型铸件的经验不足,需要快速学习曲线。
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来源期刊
CiteScore
6.30
自引率
12.90%
发文量
100
审稿时长
6 months
期刊介绍: The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications. Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping
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