{"title":"汽车工业中大型铸件几何保证的挑战","authors":"Kristina Wärmefjord, Josefin Hansen, R. Söderberg","doi":"10.1115/1.4062269","DOIUrl":null,"url":null,"abstract":"\n 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.","PeriodicalId":54856,"journal":{"name":"Journal of Computing and Information Science in Engineering","volume":"16 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Challenges in Geometry Assurance of Megacasting in the Automotive Industry\",\"authors\":\"Kristina Wärmefjord, Josefin Hansen, R. Söderberg\",\"doi\":\"10.1115/1.4062269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n 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.\",\"PeriodicalId\":54856,\"journal\":{\"name\":\"Journal of Computing and Information Science in Engineering\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computing and Information Science in Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4062269\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computing and Information Science in Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4062269","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Challenges in Geometry Assurance of Megacasting in the Automotive Industry
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.
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