Intelligent Robotic Inspection for Foundation Industry Optimisation demonstration - IRIFIO:D2

基础产业优化智能机器人检测示范 - IRIFIO:D2

• 批准号: 10030784
• 金额: $ 254.94万
• 依托单位: I3D ROBOTICS LTD
• 依托单位国家: 英国
• 项目类别: Demonstrator
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10030784
• 关键词: Intelligent; Robotic; Inspection; Foundation; Industry

This collaborative, cross sector R&D demonstration project furthers previous industrial research to advance & showcase novel technology developed to support transformation of Foundation Industry production process optimisation. The primary aim is to increase efficiency to achieve greater productivity by increased energy and resource efficiency. This will be achieved by using advanced robotics integrated with 3D machine vision systems which are augmented with bespoke sensors creating a data rich environment.The robotic, vision and sensory technology will be applied and demonstrated with foundation industry production processes building on previous R&D to digitally inspect defects in metals, glass and ceramics. With additional utilisation of machine learning (ML) on data collected, the advacned artificial intelligence (AI) developed can begin to enhance these traditional Foundation Industry production processes to enabling greater industrial productivity whilst significantly reducing energy consumption and CO2 emissions in both glass, metals, and ceramic manufacturing.Current manufacturing methods are inflexible, often requiring the time-intensive pre-programming or manual intervention of production tasks responding to unexpected occurrences or production errors. This means that foundation industries are unable to respond to the demands of future environmental targets and cannot make further improvements within the manufacturing process until the production methods are updated. This is critical to address; success will allow UK manufacturing to remain competitive when facing increasing global competition where labour rates and emissions regulations are significantly lower.This project aims to use advanced 3D vision sensor data to produce ML and AI algorithms to monitor and improve the metals, glass and ceramic production process. To guarantee the repeatability and accuracy of measurement, automation through the flexibility offered by modern multi-axis robotic systems will be demonstrated. The ultimate output of the system will result in foundation industry-wide benefits in glass, ceramics, and metals production.This project will address specific needs in these foundation industries by offering an augmented, existing manufacturing process brought about by digitised inspection & intelligent machine learning. It is anticipated that a reduction in energy costs and improved production yields associated with the manufacture of tempered glass & kiln fired ceramic materials will be significantly and positively impacted, as is the case in the foundry castings industries.

这一跨部门协作研发示范项目进一步推进了之前的工业研究，以推进和展示为支持基础工业生产流程优化转型而开发的新技术。主要目标是通过提高能源和资源效率来提高效率，从而实现更高的生产力。这将通过使用与 3D 机器视觉系统集成的先进机器人技术来实现，这些系统通过定制传感器增强，创建一个数据丰富的环境。机器人、视觉和传感技术将通过基于先前研发的基础工业生产流程进行应用和演示，以进行数字化检查金属、玻璃和陶瓷中的缺陷。通过对收集的数据进一步利用机器学习 (ML)，所开发的先进人工智能 (AI) 可以开始增强这些传统的基础工业生产流程，以实现更高的工业生产力，同时显着减少玻璃、金属、金属等行业的能源消耗和二氧化碳排放。当前的制造方法不灵活，通常需要对生产任务进行耗时的预编程或手动干预，以应对意外事件或生产错误。这意味着基础工业无法应对未来环境目标的要求，并且在生产方法更新之前无法在制造过程中进行进一步改进。这是解决这一问题的关键；成功将使英国制造业在面临日益激烈的全球竞争（劳动力价格和排放法规显着降低）时保持竞争力。该项目旨在使用先进的 3D 视觉传感器数据来生成 ML 和 AI 算法，以监控和改进金属、玻璃和陶瓷生产过程。为了保证测量的可重复性和准确性，将展示通过现代多轴机器人系统提供的灵活性实现的自动化。该系统的最终输出将为玻璃、陶瓷和金属生产带来全行业的基础效益。该项目将通过提供由数字化检测和智能机器学习带来的增强型现有制造流程来满足这些基础行业的特定需求。预计与钢化玻璃和窑烧陶瓷材料的制造相关的能源成本的降低和产量的提高将受到显着且积极的影响，就像铸造行业的情况一样。