In-Process Monitoring and Control of Computer Numerical Control Machine Tool Operations

该项目将开发使用声发射(AE)的计算机数字控制(NC)机床操作的高效率和可靠性的技术，从而导致先进的工具控制策略。机床在其使用寿命期间容易受到磨损和可能的故障，可能导致制造质量不佳的部件或部件报废。因此，四年制学员的目标是在数控加工过程中使用声发射来监控刀具，以从目前的定期磨损测量方法转变为“按需”方法，从而实现高效率并重要地防止刀具故障。该项目将详细了解在正常运行和缺陷开发过程中，由刀具和部件释放的与数控过程相关的AE特征。利用机器学习，可以识别磨损的数据询问方法将被开发出来，从而导致能够检测刀具损坏的控制系统，该控制系统将在制造过程中自动调整数控工艺。这将消除定期测量工具磨损的需要，并重要地防止工具故障，从而提高效率。

This project will develop technology to create high-efficiency and reliability in Computer Numerical Control (CNC) machine operations using Acoustic Emission (AE), leading to an advanced tool control strategy.Machine tools are subject to wear and possible failure during their operational life that can lead to poorly manufactured parts or scrapping of a component. The aim of this four year studentship is therefore to use Acoustic Emissions to monitor the tool during the CNC process to move from the current approach of periodic wear measurements to an 'as required' approach leading to high-efficiency and importantly prevent tool failure. This project will develop a detailed understanding of AE signatures associated with the CNC process, released by the tool and the component, in normal operations and during defect development. Using Machine Learning a data interrogation approach that can identify wear will be developed leading to a control system capable of detecting tool damage that will automatically adjust the CNC process during manufacture. This will aid efficiency by removing the need to periodically measure tool wear and importantly prevent tool failure.