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立和维持一个弹性和可持续的制造业，该行业能够通过调整、重新调整用途、重新安置和重新利用现有产能来应对不断变化的供需。2020年出现的大流行病影响了我们对未来制造业务的看法，特别是使在面临重大中断时交付关键产品和维持生产的能力挑战成为焦点。它还加速了一种新兴趋势，即更本地化、更环保、更具成本竞争力的本土制造业基础设施，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疫情后的挑战，我们需要变革性的新方法，通过在动态和快速变化的世界中拥抱复杂性、不确定性和数据密集度来建设和利用未来的工厂。“变形工厂”制造智能中心旨在为下一代弹性互联制造服务提供平台。它将允许未来的制造业务由无处不在的生产单位交付，这些生产单位可以根据不断变化的市场需求轻松地重新调整用途、重新定位和重新部署。这一愿景将通过3个密切相关的方面来实现：(1)基础研究计划，以确定未来工厂在架构、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的原则、方法和模型。(50%)。(2)动态的挑战驱动的应用研究计划，以满足新兴的工业需求，并通过一系列应用研究来验证和展示结果，包括智能加工、集成生产的3D打印和集成到共同的超连接变形工厂云中的自动组装(45%)。(3)与其他ISCF的联网和参与活动计划使SMART研究和创新中心、产业界和普通公众能够最大限度地发挥研究的影响，鼓励加速采用技术并提高公众意识(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