Dynamic temperature measurement and real-time monitoring for characterising material formability during straining

动态温度测量和实时监控，用于表征应变期间材料的可成形性

• 批准号: 10089588
• 金额: $ 1.91万
• 依托单位: MULTI-X SOLUTIONS LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10089588
• 关键词: Dynamic; temperature; measurement; real; time

The global metal stamping market is projected to reach a size of $278Bn by 2027, with the automotive sector accounting for 35.5% of the total. Hot formed car components are increasingly utilised in vehicles to achieve lightweight car body/chassis structures and reduce CO2 emissions. In sheet metal forming, the accurate prediction and prevention of forming-induced defects are crucial to ensure successful forming of high-quality, lightweight structural components. However, the accuracy and efficiency of process simulation for hot forming are hindered by the lack of material formability data at elevated temperatures to quantify complex straining states, resulting in high energy consumption and costs in prototyping and production.Multi-X Solutions Limited, a spin-out of Imperial College and a lifetime member of the Enterprise Hub at the Royal Academy of Engineering, provides cost-effective material testing equipment and services using invented instrumentation, methods, and developed AI (Artificial Intelligence) models for automotive applications, enabling novel quantitative measurement and evaluation of material formability properties and performance under real-life manufacturing conditions. Multi-X aims to further develop and train the Al-based deep learning platform/software for car component stamping processes using our established high-fidelity datasets.To address the challenges related to temperature distribution mapping and monitoring during the straining process, Multi-X will implement contactless temperature measurement using imaging phosphor thermometer technology from the National Physical Laboratory (NPL). This implementation will significantly enhance the value propositions of Multi-X's flagship testing service and AI tools for hot forming lightweight car components.A successful project outcome will further improve the quality assurance of Multi-X's leading material formability testing technology and generate high-fidelity datasets used for training Al tools across a wide range of sectors, including automotive, aircraft, and other public transportation industries.The ultimately goal is to standardise the developed testing method for the advancement of the data-driven manufacturing industry. The success of this project will enable accurate formability measurement for hot forming processes by providing real-life data for computer-based simulation and Al models, thereby advancing product designs and optimising manufacture processes. It will also lead to a significant reduction in development time, trial and error, and costs from product design to prototyping, while increasing productivity in hot forming. Moreover, the project aims to fully exploit material formability properties to maximise component complexity, reduce vehicle weight, and directly contribute to CO2 emissions reduction.

预计到2027年，全球金属冲压市场规模将达到2780亿美元，其中汽车行业占总量的35.5%。热成型汽车部件越来越多地应用于车辆中，以实现轻量化的车身/底盘结构并减少二氧化碳排放。在金属板材成形中，准确预测和预防成形引起的缺陷对于确保高质量、轻质结构部件的成功成形至关重要。然而，由于缺乏高温下材料的可成形性数据来量化复杂的应变状态，热成形工艺模拟的准确性和效率受到阻碍，从而导致原型设计和生产的能耗和成本较高。Multi-X Solutions Limited，一家旋转公司-来自帝国理工学院，是皇家工程院企业中心的终身会员，利用发明的仪器、方法和为汽车应用开发的 AI（人工智能）模型，提供具有成本效益的材料测试设备和服务，从而实现新颖的定量分析材料的测量和评估现实制造条件下的成形性能和性能。 Multi-X 旨在利用我们已建立的高保真数据集，进一步开发和训练用于汽车零部件冲压工艺的基于人工智能的深度学习平台/软件。为了解决应变过程中与温度分布映射和监控相关的挑战，Multi-X将利用国家物理实验室（NPL）的成像荧光温度计技术实现非接触式温度测量。此次实施将显着增强 Multi-X 的旗舰测试服务和用于热成型轻型汽车零部件的人工智能工具的价值主张。成功的项目成果将进一步提高 Multi-X 领先的材料成型性测试技术的质量保证，并生成高保真数据集用于培训各个领域的人工智能工具，包括汽车、飞机和其他公共交通行业。最终目标是标准化开发的测试方法，以促进数据驱动的制造业的进步。该项目的成功将为基于计算机的仿真和人工智能模型提供真实数据，从而实现热成型工艺的精确成型性测量，从而推进产品设计并优化制造工艺。它还将显着减少开发时间、试验和错误以及从产品设计到原型制作的成本，同时提高热成型的生产率。此外，该项目旨在充分利用材料的成型性能，最大限度地提高部件复杂性，减轻车辆重量，并直接有助于减少二氧化碳排放。