## 4 Discussion  
An active field of study is the investigation of inspecting additive manufactured parts. One of the features of this current manufacturing process is the method of build, where shaped material is added, often in layers--this makes the process available for surface-based inspection on the bulk material if measurements are conducted in-process. Very few non-destructive evaluation techniques are suited to taking rapid measurements of defects inside an AM build environment. These defects include newly created subsurface voids created by keyholing effects--sizing and locating the features could become important when considering defect density rather than singular defects. This paper introduces a SRAS system capable of detecting surface ultrasound waves on the rough-surface of an as-deposited SLM sample. The system is an all-optical implementation, which does not require instrument contact for measurement and is capable of detecting subsurface defects [10]. The primary market for AM tool manufacturing is the high-value sector (e.g., aerospace), where microstructure information for high-performance is required by the end user. The described inspection system is also capable of imaging material texture on an as-deposited sample. The work presented in this paper, comprising the rough-surface SRAS setup and the SLM chamber integrated SRAS system, illustrates the potential that this system has in performing in-situ part defect and material characterisation. For a practical implementation, there are a number of challenges  
Figure 9: Photographs of the SLM-integrated SRAS system, (**a**) fully enclosed (class 1 laser safe), (**b**) plan view of the SRAS setup, with components and beam path indicated, (**c**) a T64 SLM strip under inspection on a large build plate, (**d**) the signal obtained on the SLM sample on an oscilloscope. Aluminium plates, rubber seals and interlocks were designed into the enclosure as this SLM-SRAS chamber is intended to be a demonstration unit. The optical setup was positioned in a similar area to the actual SLM machine’s optics train. New software had been written to control acquisition and translation. The optics seen in the build chamber (**c**) were used to monitor the incident light and are not required to perform the SRAS inspection. to overcome. A raster scanning strategy is employed, where it is possible to collect single-shot SRAS waveform measurements (roughly 1500 points per second) [18]. This is a slower measurement capture time when compared to inspection systems based on camera arrays (e.g., thermography, metrology). Additionally, limitations of this optical arrangement exist where the light intensity incident on the detector is greatly reduced due to the diffuse reflection. A number of averages is required to improve SNR, further increasing scan times. The spatial resolution of the optical and acoustic images can be defined using the detection beam size and generation patch size on the surface, respectively--providing a singular answer for the size and depths of subsurface defects becomes a challenge [35]. Lamb wave ultrasound inspection of single crystal materials has been investigated by the authors [36; 37], with recent work published on imaging defects in carbon-fibre reinforced plastic materials [38]--for use in additive manufacturing, the anisotropy of the material will determine whether a subsurface pore can be distinguished. If a material is isotropic, detecting defects close to the surface (within 2\(\lambda_{g}\)) should be as resolvable as the material microstructure, with deeper defects having a lesser effect on the velocity measured. Conceptualisation, R.L. and S.S.; Methodology, R.P., M.H. and S.A.-Y. ; Software, R.P., M.H., P.D., S.A.-Y., R.L., S.S. and M.C. ; Validation, R.P. ; Investigation, R.P., D.P. and S.A.-Y. ; Resources, M.H. ; Data Curation, R.P. and S.A.-Y. ; Writing--Original Draft Preparation, R.P. ; Writing--Review & Editing, R.P., P.D., R.S., R.L., S.S., A.C. and M.C. ; Supervision, R.S., S.A.C. and M.C. ; Funding Acquisition, S.S. and A.C.