Brokering Additive Manufacturing
Brokering Additive Manufacturing
批准号:
EP/V05113X/1
负责人:
James Gopsill
金额:
$96.71万
依托单位:
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
项目状态:
已结题
起止时间:
2021 至 --
中文摘要
社会正在推动对响应式制造的需求,并且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,批量和准时制)。驱动因素1是大需求,这涉及到大型事件(如COVID-19、英国脱欧、灾难应对、全球金融危机和战争)产生的需求的响应、数量、种类和位置,以及大规模定制/定制产品(如汽车生产线和供应链)根本无法满足MPP,因为它们已经针对特定产品进行了优化。驱动程序2适应动态生产约束。COVID-19的社会距离和分级制度措施以及贸易争端(英国脱欧和美国与中国)表明,MPP可以很快被切断,大大减少了对社会的供应。驱动因素三是促进制造业的独立性。MMP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,许多社会将制造业独立视为战略目标(例如回流),特别是考虑到驱动因素1和2,一个国家依赖其他国家的制造能力使他们脆弱,没有能力满足他们的国家需求。代理增材制造(BAM)将证明,如果能够有效地进行代理,可以通过一个国家高度分散和多样化的增材制造(AM)能力来满足这些驱动因素。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)以及行业/政府计划(Reshoring UK)的300多位领导者,以创建高度分布式和多样化制造系统的新型代理。BAM的跨学科方法将使团队:描述巨大的需求、动态的生产限制以及地方、区域、国家和全球背景,以促进独立。2. 开发商业模式和政府政策。表征调幅能力。4. 创建生产系统边界条件模型和基于代理的BAM模型,模拟社区、区域、国家和国际尺度上的人和机器工作中介。BAM解决方案将通过控制实验室实验、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型的生产系统,它可以代理高度分散和多样化的制造能力(例如AM)。这将支持未来的工厂,这些工厂不再局限于单一的设施,而是像它们所容纳的制造能力一样多样化和分布,彻底改变社会的生产方式,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。
英文摘要
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.
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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
期刊:
影响因子:
--
作者:
[Gopsill J]
通讯作者:
Gopsill J
DOI:
10.1017/pds.2022.43
发表时间:
2022-05
期刊:
Proceedings of the Design Society
影响因子:
--
作者:
[L. Giunta;J. Gopsill;L. Kent;M. Goudswaard;C. Snider;B. Hicks]
通讯作者:
L. Giunta;J. Gopsill;L. Kent;M. Goudswaard;C. Snider;B. Hicks
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
影响因子:
--
作者:
[Cox C]
通讯作者:
Cox C
DOI:
10.14733/cadconfp.2022.134-139
发表时间:
2022
期刊:
影响因子:
--
作者:
[Cox C]
通讯作者:
Cox C
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