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，英国明显落后于其他国家。直接与人合作的协作自动化为加强英国制造业和重建英国经济提供了绝佳的机会。它将帮助企业提高生产力，在面临保护就业和增长的外部压力（如 ​​Covid-19 大流行）时更具响应能力和弹性。为了实现对自动化的自信投资，我们需要克服当前的基本障碍。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，并以现有工人和更广泛的社会欢迎的方式发展为安全、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) 与业界合作，确定了四个优先研究领域：协作、自主、简单、接受。最初的计划将解决每个领域当前的基本挑战，并开发测试平台以展示结果。在该计划过程中，CESCIR 还将开展响应式研究，快速测试新想法，以解决现实世界的制造自动化挑战。 CESCIR 将创建一个学术界和工业界网络，连接利益相关者，识别挑战/机遇，审查进展并分享结果。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，由于自动化可以引入传统的手动生产流程，大型企业将受益。同样，更好的可访问性和敏捷性将使更多的中小企业 (SME) 从自动化中受益，从而提高其在全球市场中的竞争力。

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