UK consortium wins Innovate UK grant for research and development on NDT in metal additive manufacturing
03/06/2019
A consortium comprising ETher NDE (St Albans), Sonemat (Coventry), Hybrid Manufacturing Technologies (Moira), Innvotek (London), Brunel Innovation Centre (Abington) and TWI (Abington) has won a grant to develop technology to inspect metal additive manufactured parts during the manufacturing process. The technology uses electromagnetic methods (electromagnetic acoustic transducer (EMAT) and eddy current (EC)) to detect defects and to monitor residual stress in additive manufacturing (AM) and is abbreviated as EM-ReSt.Metal AM is an emerging technology for the fabrication of high-value parts in low- to medium-part volumes. Notable early adoption in aerospace, medical and power generation industries is due to AM’s capability for producing complex geometry and multi-material parts. The safety-critical nature of existing and potential applications for parts made using AM requires a high level of certainty that the integrity of the part will meet relevant specifications and standards. In several metal AM techniques, including powder-bed fusion and directed energy deposition, unmanaged residual stress and microcracking can occur during the manufacturing process. This can predispose printed parts to structural failure of the object after its manufacture. To leverage the benefits of AM, it is imperative that any faults that may occur during manufacturing due to incorrect processing conditions or environmental variability be corrected and eliminated. To that end, a convenient and cost-effective rapid assessment method is needed.
The nature of some AM methods means that not all non-destructive testing (NDT) techniques are effective in detecting residual stress. Thermography, X-ray computed tomography (CT) and digital radiography are limited by the resolution of images (thermography), are bulky and costly (up to £100,000) and are not ideally suited to in-situ residual stress detection. The solution, EM-ReSt, functions as an add-on to existing AM processes and comprises two sets of NDT techniques: EMATs and eddy current testing (ECT). A crucial (and novel) extension of the proposed system is the incorporation of big data collection from the sensors and analysis through machine learning (ML) to estimate the likelihood of the AM techniques introducing anomalies into the printed structures before the beginning of the manufacturing. A digital system that estimates the potential and deficiencies of any AM technique for given structures will be developed and utilised for the establishment of a preliminary set of AM standards. Hence, more robust and reliable components will be printed and used.EM-ReSt offers fast, reliable non-destructive online monitoring of AM techniques, which can achieve a significant reduction in faulty outputs with the use of a more cost-effective monitoring system incorporating low-profile sensing hardware with the potential for EMAT and EC miniaturisation. The initial target markets are the global aerospace, automotive component and power generation manufacturing industries. This project represents a clear technological innovation for AM users worldwide from this agile UK-based consortium.
The project has a short end-user survey available at: https://forms.gle/zWzQyQtmzVNqDjms9 and all participants are welcome. A printable version can be obtained by emailing john@ethernde.com
