Made Smarter Innovation - Research Centre for Smart, Collaborative Industrial Robotics

更智能的创新 - 智能协作工业机器人研究中心

• 批准号: EP/V062158/1
• 负责人: Niels Lohse
• 金额: $ 614.37万
• 依托单位: Loughborough University
• 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%2FV062158%2F1
• 关键词: Made; Smarter; Innovation; Research; Centre

The UK has fallen significantly behind other countries when it comes to adopting robotics/automation within factories. Collaborative automation, that works directly with people, offers fantastic opportunities for strengthening UK manufacturing and rebuilding the UK economy. It will enable companies to increase productivity, to be more responsive and resilient when facing external pressures (like the Covid-19 pandemic) to protect jobs and to grow.To enable confident investment in automation, we need to overcome current fundamental barriers. Automation needs to be easier to set up and use, more capable to deal with complex tasks, more flexible in what it can do, and developed to safely and intuitively collaborate in a way that is welcomed by existing workers and wider society. To overcome these barriers, the ISCF Research Centre in Smart, Collaborative Robotics (CESCIR) has worked with industry to identify four priority areas for research: Collaboration, Autonomy, Simplicity, Acceptance. The initial programme will tackle current fundamental challenges in each of these areas and develop testbeds for demonstration of results. Over the course of the programme, CESCIR will also conduct responsive research, rapidly testing new ideas to solve real world manufacturing automation challenges. CESCIR will create a network of academia and industry, connecting stakeholders, identifying challenges/opportunities, reviewing progress and sharing results. Open access models and data will enable wider academia to further explore the latest scientific advances. Within the manufacturing industry, large enterprises will benefit as automation can be brought into traditionally manual production processes. Similarly, better accessibility and agility will allow more Small and Medium sized Enterprises (SMEs) to benefit from automation, improving their competitiveness within the global market.

在工厂采用机器人/自动化方面，英国远远落后于其他国家。协同自动化直接与人们合作，为加强英国制造业和重建英国经济提供了绝佳的机会。它将使企业能够提高生产力，在面临外部压力（如新冠肺炎疫情）时更迅速地做出反应，更有弹性地保护就业和实现增长。为了让人们对自动化充满信心，我们需要克服当前的根本障碍。自动化需要更容易设置和使用，更有能力处理复杂的任务，更灵活地执行任务，并以受现有工人和更广泛社会欢迎的方式进行安全和直观的协作。为了克服这些障碍，ISCF智能协作机器人研究中心（CESCIR）与工业界合作，确定了四个优先研究领域：协作，自主，简单，接受。初步方案将解决这些领域中每一个领域目前面临的基本挑战，并开发试验平台以展示成果。在该计划的过程中，CESCIR还将进行响应性研究，快速测试新的想法，以解决真实的世界制造自动化的挑战。CESCIR将建立一个学术界和工业界的网络，连接利益相关者，确定挑战/机遇，审查进展和分享成果。开放获取模型和数据将使更广泛的学术界能够进一步探索最新的科学进展。在制造业中，大型企业将受益，因为自动化可以引入传统的手工生产过程。同样，更好的可访问性和灵活性将使更多的中小型企业（SME）受益于自动化，提高其在全球市场上的竞争力。

项目成果

Object Shape Error Modelling and Simulation During Early Design Phase by Morphing Gaussian Random Fields

• DOI: 10.1016/j.cad.2023.103481
• 发表时间: 2020-10
• 期刊: Comput. Aided Des.
• 作者: Manoj Babu;P. Franciosa;Prashant Shekhar;D. Ceglarek

Fusing optical coherence tomography and photodiodes for diagnosis of weld features during remote laser welding of copper-to-aluminum

• DOI: 10.2351/7.0000803
• 发表时间: 2023-02
• 期刊: Journal of Laser Applications
• 影响因子: 2.1
• 作者: Tine Brežan;P. Franciosa;M. Jezeršek;D. Ceglarek

Degenerate boundaries for multiple-alternative decisions.

• DOI: 10.1038/s41467-022-32741-y
• 发表时间: 2022-08-29
• 期刊: Nature communications
• 影响因子: 16.6

Understanding Deepfakes: A Comprehensive Analysis of Creation, Generation, and Detection

了解 Deepfakes：对创建、生成和检测的综合分析

• DOI: 10.54941/ahfe1003290
• 发表时间: 2023
• 作者: Alanazi S

A multi-physics CFD study to investigate the impact of laser beam shaping on metal mixing and molten pool dynamics during laser welding of copper to steel for battery terminal-to-casing connections

• DOI: 10.1016/j.jmatprotec.2023.118202
• 发表时间: 2023-10
• 期刊: Journal of Materials Processing Technology
• 影响因子: 6.3
• 作者: Giovanni Chianese;Qamar Hayat;S. Jabar;P. Franciosa;Dariusz Ceglarek;S. Patalano