Adaptive Self Learning Robotic Linishing and Polishing

自适应自学习机器人抛光

• 批准号: 10075612
• 金额: $ 20.49万
• 依托单位: ADVANCED AEROSPACE ASSEMBLY LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10075612
• 关键词: Adaptive; Self; Learning; Robotic; Linishing

_Variability_ _is traditionally the enemy of automation__, but with today's focus on customisation and choice this needs to change. To be widely used and adopted across UK manufacturing. automation must be able to handle large dimensional changes and be capable of changing quickly and effectively between different operations. This project addresses this issue with the development and application of an adaptive path planning system that will alter the pre-set robot program whilst in use so that changes in part shape and size can be accommodated.__A technology demonstrator of an automated linishing and polishing_ _automation cell will be built_ _to highly polish plastic parts. The system will have the capability to measure and react to the size, shape and requirements of the part to be processed thereby making it self-programming and adapting.__Blanson_ _are a manufacturer of highly engineered acrylic parts and will be supported by two SME, robotic technology partners, A3L and HAL Robotics. A3L are robotic integrators focused on delivering automated finishing operations to SME's but they hope to become a high-end global supplier of automated finishing solutions. HAL Robotics are specialists in adaptive robot path planning, their software Framework allows the use of sensor or/and measurement data to alter robot programs 'on the fly' thereby allowing for the process to be flexible and controlled by the attributes of the part._ A3L will work together with HAL to deliver an innovative finishing solution that can be utilised within Blanson's manufacturing facility. We are aiming for a 'one size fits all' approach to finishing automation, i.e., the system will be able to process multiple parts without reprogramming. It will utilise sensor data to determine where the process needs to be applied and when it is complete i.e., surface roughness or part geometry readings will be fed back into a software solution which will determine fitness and automatically generate any necessary corrective robot toolpaths. AI will also be used to process data to optimise use of abrasive consumables. Current best practice is to use the abrasives for a set time period and then dispose of them (whether they are spent or not), we believe the volume of consumables used monthly can be greatly reduced delivering huge cost savings and driving a greener approach.

_ variability _ _传统上是自动化__的敌人，但由于今天的重点是自定义和选择，这需要改变。在英国制造业中广泛使用和采用。自动化必须能够处理大大的变化，并能够在不同操作之间快速有效地变化。该项目通过使用自适应路径计划系统的开发和应用来解决此问题，该系统将在使用中更改预设的机器人程序，以便可以容纳零件形状和尺寸的变化。将建立细胞_ _高度抛光塑料零件。该系统将有能力对要处理的零件的大小，形状和要求进行衡量和反应技术合作伙伴，A3L和HAL机器人技术。 A3L是专注于为中小型企业提供自动完成操作的机器人集成商，但他们希望成为自动化饰面解决方案的高端全球供应商。 HAL Robotics是自适应机器人路径计划中的专家，其软件框架允许使用传感器或/和测量数据来更改机器人程序“飞行”，从而使该过程具有灵活性和受部分属性的控制。 A3L将与HAL一起提供创新的饰面解决方案，该解决方案可以在Blanson的制造工厂中使用。我们的目标是“一种尺寸适合所有”方法来完成自动化，即系统将能够处理多个部分而无需重新编程。它将利用传感器数据来确定需要在何处应用过程以及完成何时完成，即表面粗糙度或零件几何读数将被送回软件解决方案，该解决方案将确定适合度并自动生成任何必要的纠正式机器人工具路径。 AI还将用于处理数据以优化使用磨料消耗品的使用。当前的最佳实践是在设定的时间段中使用磨料，然后处理它们（无论是花费的），我们相信每月使用的消耗品的数量可以大大减少，以节省大量成本并推动更绿色的方法。