Made Smarter Innovation - Research Centre for Connected Factories

更智能的创新 - 互联工厂研究中心

• 批准号: EP/V062123/1
• 负责人: Svetan Ratchev
• 金额: $ 648.8万
• 依托单位: University of Nottingham
• 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: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV062123%2F1
• 关键词: Made; Smarter; Innovation; Research; Centre

The future prosperity of the UK will increasingly depend on building and maintaining a resilient and sustainable manufacturing sector that can respond to changing supply and demand by adapting, repurposing, relocating and reusing available production capabilities. The pandemic which emerged in 2020 has influenced our perspective of future manufacturing operations and, in particular, has brought into focus the capacity challenges of delivering critical products and maintaining production in the face of major disruptions. It also accelerated the emerging trend for more localised, greener and cost-competitive indigenous manufacturing infrastructure with the ability to produce a wider set of complex products faster, better and cheaper. To meet the long-term structural and post-pandemic challenges, we need transformative new methods of building and utilising future factories by embracing complexity, uncertainty and data intensity in a dynamic and rapidly changing world.The "Morphing Factory" Made Smarter Centre aims to deliver a platform for next generation resilient connected manufacturing services. It will allow future manufacturing operations to be delivered by ubiquitous production units that can be easily repurposed, relocated and redeployed in response to changing market demand. This vision will be delivered through 3 closely related strands: (1) An underpinning fundamental research programme to define the principles, methods and models for future morphing factories in terms of architecture, topology, configuration methods, IoT digital awareness, in-process monitoring and AI based autonomous control. (50%). (2) A dynamic challenge-driven applied research programme to address emerging industrial needs and validate and demonstrate the results through a set of application studies including smart machining, production integrated 3D printing and autonomous assembly integrated into a common hyperconnected morphing factory cloud (45%). (3) A programme of networking and engagement activities with other ISCF Made Smarter research and innovation centres, industry and the general public to maximise the impact of the research, encourage accelerated technology uptake and increase the public awareness (5%).

英国未来的繁荣将越来越依赖于建设和维持一个有弹性和可持续的制造业，该制造业可以通过调整、重新调整、重新定位和重用现有生产能力来应对不断变化的供需。 2020 年出现的疫情影响了我们对未来制造运营的看法，特别是让我们关注在面临重大中断时交付关键产品和维持生产的产能挑战。它还加速了更加本地化、更加环保和具有成本竞争力的本土制造基础设施的新兴趋势，能够更快、更好、更便宜地生产更广泛的复杂产品。为了应对长期的结构性挑战和大流行后的挑战，我们需要通过拥抱动态和快速变化的世界中的复杂性、不确定性和数据强度来建设和利用未来工厂的变革性新方法。“变形工厂”变得更智能中心旨在为下一代弹性互联制造服务提供一个平台。它将允许未来的制造业务由无处不在的生产单元提供，这些生产单元可以轻松地重新调整用途、重新定位和重新部署，以响应不断变化的市场需求。这一愿景将通过三个密切相关的方面来实现：（1）基础研究计划，从架构、拓扑、配置方法、物联网数字感知、过程监控和基于人工智能的自主控制方面定义未来变形工厂的原理、方法和模型。 （50%）。 (2) 一个动态挑战驱动的应用研究项目，旨在解决新兴的工业需求，并通过一系列应用研究来验证和展示结果，包括智能加工、生产集成 3D 打印和集成到通用超连接变形工厂云中的自主装配 (45%)。 (3) 与其他 ISCF Made Smarter 研究和创新中心、行业和公众建立联系和参与活动的计划，以最大限度地发挥研究的影响，鼓励加速技术采用并提高公众意识 (5%)。

项目成果

Mobile Robots for In-Process Monitoring of Aircraft Systems Assemblies.

• DOI: 10.3390/s22093362
• 发表时间: 2022-04-27
• 期刊: Sensors (Basel, Switzerland)

Deep learning enabled error detection and correction for 3D printing

深度学习支持 3D 打印的错误检测和纠正

• DOI: 10.17863/cam.100129
• 发表时间: 2023
• 作者: Brion D

Quantitative and Real-Time Control of 3D Printing Material Flow Through Deep Learning

• DOI: 10.1002/aisy.202200153
• 发表时间: 2022-09-11
• 期刊: ADVANCED INTELLIGENT SYSTEMS
• 影响因子: 7.4
• 作者: Brion, Douglas A. J.;Pattinson, Sebastian W.
• 通讯作者: Pattinson, Sebastian W.

Augmented Reality for Quality Inspection: A User-Centred Systematic Review of Use Cases, Trends and Technology

• DOI: 10.1109/ismar-adjunct60411.2023.00038
• 发表时间: 2023-10
• 期刊: 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)
• 作者: Alexander Albers;Thomas Bohné;S. Tadeja

Towards Augmented Reality Guiding Systems: An Engineering Design of an Immersive System for Complex 3D Printing Repair Process

迈向增强现实引导系统：复杂 3D 打印修复过程的沉浸式系统的工程设计

• DOI: 10.1109/vrw58643.2023.00084
• 发表时间: 2023
• 作者: Bozzi L