Brokering Additive Manufacturing

经纪增材制造

• 批准号: EP/V05113X/1
• 负责人: James Gopsill
• 金额: $ 96.71万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV05113X%2F1
• 关键词: Brokering; Additive; Manufacturing

Society is driving the need for Responsive Manufacturing and requires fundamental research to come-up with strategies that can complement existing Modern Manufacturing Practice (MPP) (e.g. batch, mass and just-in-time). Driver 1 is Big Demand, which concerns the response, volume, variety and location in demand, arising from large-scale events, such as COVID-19, Brexit, Disaster Response, Global Financial Crisis and War, and mass-customisation/bespoke products simply cannot be met by MPP, such as automotive production lines and supply chains, as they have been optimised for particular products. Driver 2 is accommodating dynamic production constraints. COVID-19's measures of social distancing and tiering system as well as trade disputes (Brexit and America vs. China) have shown how quickly MPP can be severed, significantly reducing supply to society. Driver 3 is facilitating manufacturing independence. MMP has enabled large developed nations - America, China, EU, Japan, South Korea, India - to provide production capability that developed smaller (e.g. UK, Switzerland) and developing nations would not have had access to. However, many society's view manufacturing independence as a strategic goal (e.g. Reshoring) especially in light of Drivers 1 & 2 where a nations reliance on other nations' manufacturing capability leaves them vulnerable and without the capability to combat their national needs.Brokered Additive Manufacturing (BAM) will prove that these drivers can be met through a nation's highly distributed and diverse Additive Manufacturing (AM) capability if it can be effectively brokered. BAM brings together world-leading researchers from the Schools of Civil, Mechanical and Aerospace engineering and Business Management, 300+ leaders in the AM industry (GTMA, AMUG, AT 3D Squared) and Model-Based Systems Engineering (CFMS), and industry/government initiatives (Reshoring UK) to create novel brokering of highly distributed and diverse manufacturing systems. BAM's transdisciplinary approach will see the team: 1. profile Big Demand, dynamic production constraints and local, regional, national and global contexts to facilitate independence. 2. develop Business Models and Government Policy. 3. characterise AM capability. 4. create Production System boundary condition models and agent-based models of BAM that simulate both human and machine brokering of jobs at community, regional, national and international scales. BAM solutions will be evaluated through controlled lab experiments, living labs and development of industry demonstrators. The solutions will give rise to a new class of production system that broker highly distributed and diverse manufacturing capability (e.g. AM). This will underpin factories of the future that are not confined to single facilities but are as diverse and distributed as the manufacturing capability they house, revolutionising society's production giving it greater flexibility and responsiveness to meet our future needs.

社会正在推动对响应式制造的需求，并需要基础研究来提出可以补充现有现代制造实践（MPP）的策略（例如批量，大规模和即时）。驱动因素一是大需求，涉及大规模事件（如COVID-19、英国脱欧、灾难应对、全球金融危机和战争）所产生的需求的响应、数量、种类和位置，而大规模定制/定制产品（如汽车生产线和供应链）根本无法通过MPP满足，因为它们已针对特定产品进行了优化。驱动因素2适应动态生产约束。COVID-19的社交距离和分层系统以及贸易争端（英国脱欧和美国与中国）的措施表明MPP可以多么迅速地被切断，大大减少了对社会的供应。驱动因素3是促进制造独立性。微型企业方案使大型发达国家-美国、中国、欧盟、日本、韩国、印度-能够提供较小的发达国家（如英国、瑞士）和发展中国家无法获得的生产能力。然而，在这方面，许多社会将制造业独立视为一个战略目标（例如，回归）特别是考虑到驱动因素1和2，一个国家对其他国家制造能力的依赖使他们变得脆弱，没有能力满足其国家需求。代理增材制造（BAM）将证明这些驱动因素可以通过一个国家的高度分布和多样化的增材制造（AM）来满足。能力，如果能够有效地发挥作用。BAM汇集了来自土木，机械和航空航天工程和商业管理学院的世界领先的研究人员，AM行业（GTMA，AMUG，AT 3D Squared）和基于模型的系统工程（CFMS）的300多位领导者，以及行业/政府计划（Reshoring UK），以创建高度分布式和多样化制造系统的新型经纪人。BAM的跨学科方法将看到团队：1。分析大需求、动态生产限制以及地方、区域、国家和全球背景，以促进独立性。2.制定商业模式和政府政策。3.的能力。4.创建BAM的生产系统边界条件模型和基于代理的模型，模拟社区，区域，国家和国际范围内的人类和机器中介工作。BAM解决方案将通过受控实验室实验、生活实验室和行业示范开发进行评估。这些解决方案将产生一种新的生产系统，这种系统可以代理高度分布式和多样化的制造能力（例如AM）。这将支撑未来的工厂，这些工厂不局限于单一的设施，而是与它们所拥有的制造能力一样多样化和分布式，彻底改变社会的生产，使其具有更大的灵活性和响应能力，以满足我们未来的需求。

项目成果

Design Computing and Cognition'22

设计计算和认知22

• DOI: 10.1007/978-3-031-20418-0_43
• 发表时间: 2023
• 作者: Gopsill J

Pro2Booth: Towards an Improved Tool for Capturing Prototypes and the Prototyping Process

• DOI: 10.1017/pds.2022.43
• 发表时间: 2022-05
• 期刊: Proceedings of the Design Society
• 作者: L. Giunta;J. Gopsill;L. Kent;M. Goudswaard;C. Snider;B. Hicks

Optimal configurations of Minimally Intelligent additive manufacturing machines for Makerspace production environments

• DOI: 10.1017/s0890060423000239
• 发表时间: 2024-01-17
• 期刊: AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING
• 影响因子: 2.1
• 作者: Gopsill，James;Goudswaard，Mark;Hicks，Ben
• 通讯作者: Hicks，Ben

Improving Mixed-Reality Prototyping through a Classification and Characterisation of Fidelity

通过保真度的分类和表征改进混合现实原型设计

• DOI: 10.1017/pds.2022.37
• 发表时间: 2022
• 期刊: Proceedings of the Design Society
• 作者: Cox C

Analysing the Variance and Sustainability of a Digital Thread

分析数字主线的差异和可持续性

• DOI: 10.14733/cadconfp.2022.134-139
• 发表时间: 2022
• 作者: Cox C