Manufacturing Fellowship Extension in: Controlling geometrical variability of products in the digital and smart manufacturing era

制造奖学金扩展领域：控制数字和智能制造时代产品的几何变异性

• 批准号: EP/R024162/1
• 负责人: Paul Scott
• 金额: $ 88.91万
• 依托单位: University of Huddersfield
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR024162%2F1
• 关键词: Manufacturing; Fellowship; Extension; Controlling; geometrical

This fellowship proposal is a three year extension of the current EPSRC manufacturing fellowship: Controlling Geometrical Variability of Products for Manufacturing (EP/I033424/1). The current fellowship is exploring the mathematical fundaments for the decomposition of geometry (i.e. size, shape and texture) and creating ground-breaking technology to control geometrical variability in manufactured products. The approach links fundamental geometrical mathematics direct to key component's design, manufacturing and verification from different industrial sectors (i.e. aerospace, optics, healthcare and catapult centres). In this case, the different types of geometrical decompositions specified geometrical surface requirements (spectrum, morphological and segmentation decompositions). The fellowship extension proposal will take the research results from the current fellowship and use them as a stepping stone for more advanced fundamental research in new areas within the manufacturing value chain. The research work is broken down to four aspects:1. Different aspects of the manufacturing process leave different multi-scalar geometrical features, in a surface, at different scales (i.e. size, shape and texture). By decomposing these different signature features, information regarding different manufacturing aspects can be gained enabling characterisation and control of different aspects of the manufacturing process.2. Sensor network provide information in the form of an irregular image, like a cubist painting, with different views, and times, of the environment all combined together. Decomposition of this information will provide access to features, and their relationships enabling an agile dynamic predictive model to be self-aware of its environment enabling mathematical foundations for bio-inspired feedback control loops from sensor networks to be developed.3. Smart autonomous manufacturing will require access to the huge amassed manufacturing knowledge-base (National and International Standards, Materials data-sheets, etc.). Create the foundations of decomposition of information structures for the automatic creation of smart information systems that are machine readable and to apply this result to develop the full rigorous mathematical foundations for the manufacturing value chain. 4. Using the EPSRC Future HUB in Advanced Metrology (EP/P006930/1) as leverage, disseminate the results from the above to solve real industrial problems to demonstrate the advantage of using fundamental decomposition theory, as developed in the previous manufacturing fellowship and this extension, over traditional approaches.

该奖学金提案是当前EPSRC制造奖学金的三年扩展：控制制造产品的几何变变性（EP/I033424/1）。目前的研究项目正在探索几何分解（即尺寸、形状和纹理）的数学基础，并创造突破性的技术来控制制造产品的几何变化。这种方法将基本的几何数学直接与不同工业部门（即航空航天、光学、医疗保健和弹射中心）的关键部件的设计、制造和验证联系起来。在这种情况下，不同类型的几何分解指定几何表面要求（光谱、形态和分割分解）。奖学金延期提案将利用当前奖学金的研究成果，并将其作为在制造业价值链新领域进行更先进的基础研究的垫脚石。本文的研究工作分为四个方面：1。制造过程的不同方面在一个表面上以不同的尺度（即尺寸、形状和纹理）留下不同的多标量几何特征。通过分解这些不同的签名特征，可以获得关于不同制造方面的信息，从而能够对制造过程的不同方面进行表征和控制。传感器网络以不规则图像的形式提供信息，就像立体主义绘画一样，将环境的不同观点和时间结合在一起。这些信息的分解将提供对特征的访问，以及它们之间的关系，从而使敏捷的动态预测模型能够自我意识到其环境，从而为来自传感器网络的生物反馈控制回路提供数学基础。智能自主制造将需要访问庞大的制造知识库（国家和国际标准，材料数据表等）。创建信息结构分解的基础，用于自动创建机器可读的智能信息系统，并应用此结果为制造价值链开发完整的严格数学基础。4. 利用EPSRC未来高级计量中心（EP/P006930/1）作为杠杆，传播上述结果以解决实际工业问题，以展示使用基本分解理论的优势，如在以前的制造奖学金和此扩展中开发的那样，优于传统方法。

项目成果

A new partitioning process for geometrical product specifications and verification

• DOI: 10.1016/j.precisioneng.2019.12.009
• 发表时间: 2020-03-01
• 期刊: PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
• 影响因子: 3.6
• 作者: Cai, Na;Anwer, Nabil;Jiang, Xiangqian
• 通讯作者: Jiang, Xiangqian

A Comparison of Least-Squares Methods Applied on Form Removal in Metrology with Application Guidelines

计量学中形状去除中应用的最小二乘法与应用指南的比较

• DOI: 10.1109/icac57885.2023.10275213
• 发表时间: 2023
• 作者: Cui W

INVESTIGATE GEOMETRY AND SURFACE TEXTURE OF SELECTIVE LASER MELTING BUILT INTERNAL CHANNELS WITH VARYING INCLINATION ANGLES USING XCT

使用 XCT 研究不同倾角的选择性激光熔化内置内部通道的几何形状和表面纹理

• 发表时间: 2022
• 期刊: 2022 ASPE and euspen Summer Topical Meeting on Advancing Precision in Additive Manufacturing
• 作者: Liu W.

Feature-based characterisation of surface topography and its application

• DOI: 10.1016/j.cirp.2021.05.001
• 发表时间: 2021-08-31
• 期刊: CIRP ANNALS-MANUFACTURING TECHNOLOGY
• 影响因子: 4.1
• 作者: Jiang, Xiangqian;Senin, Nicola;Blateyron, Francois
• 通讯作者: Blateyron, Francois

CIRP Encyclopedia of Production Engineering

CIRP生产工程百科全书

• DOI: 10.1007/978-3-642-35950-7_16863-1
• 发表时间: 2019
• 作者: Jiang X