# Imaging Microstructure on Optically Rough Surfaces Using Spatially Resolved Acoustic Spectroscopy
## 4 Discussion and Conclusions
### Scan Speed Compared to Manufacturing Speed  
An obvious question to ask is what the speed of an SRAS scan is. Whilst it is plain that a 'fast' scan is more amenable to integration within a manufacturing process, some context can be provided by using L-PBF as worked example. This allows the speed of an SRAS scan to be compared to the speed of the AM deposition. Whilst the example herein focuses on L-PBF, a similar methodology could be applied to other methods of additive manufacturing or machining, so long as the processing rates of the manufacturing operation are known.  
[PERSON] et al. developed a model for assessing the economic impact of in silico monitoring tools in AM [3]. The authors conducted a series of studies to estimate the failure rate of typical AM components. They then calculated the break-even point of a hypothetical inspection system as a function of this failure rate. The conclusion was an estimation that \(\sim\)9% savings in the cost of additive components could be achieved by the use of in silico monitoring. All of the tools the authors considered were passive, observing the emission spectra of the build process. These are essentially 'free' measurements in that there is no temporal impact on the build; therefore, only the cost of the equipment needs to be considered. However, a prospective SRAS system will need to scan the sample, causing some addition to the manufacturing time, hence the importance of the time element of the model compared to those in the existing literature. To generate the build time information shown below, a sample build similar to the Airbus A320 nacelle hinge bracket discussed in the work of [PERSON] and [PERSON] [48] was defined. This bracket was later used by [PERSON] et al. as a case study example in the aforementioned study [3]. The part takes approximately 36 h to fabricate.  
To estimate the time spent inspecting the sample build, the'speed' of the inspection system must be defined. The'speed' of the SRAS system can be essentially broken down into the rate of data acquisition and the number of data points to be captured. The speed of acquisition is a function of the number of averages required and the repetition rate of the generation laser. The number of points to be captured is primarily dependent on the size of the specimen and the acoustic wavelength (as this in turn defines the spatial resolution). Figure 13 plots the impact on build time as a function of points acquired per second and the wavelength of inspection. To give some context, parameters from the results presented earlier in this paper are marked on this figure.  
The closer to one the ratio is, the smaller the impact of inspection on the total build time. On first inspection, it would seem desirable to work as close to the lower right-hand side as possible in order to minimise the temporal penalty of inspection; however, increasing the wavelength of inspection leads to a decreased resolution and decreased measurement fidelity. The discontinuities arise because with increasing wavelength, more build layers can be inspected per scan. Therefore, increasing the acquisition rate of the SRAS system is the preferable way to increase scan speeds. The number of parameter points per second shown in Figure 13 is simply \(\frac{\text{rep rate}}{\text{averages}}\).  
On a smooth surface, the primary influence on the points per second is the repetition rate of the generation laser. In the 'on-the-fly' scanning approach [16], as used by the smooth surface system, one pulse is equivalent to one measurement point--thus, a 5 kHz repetition rate laser allows 5000 measurements per second. However, on rough surfaces, the signal-to-noise ratio (SNR) is significantly lower and necessitates averaging of the acoustic waveform to improve SNR.  
It would be preferable to correlate the number of averages needed with surface roughness and integrate this within the model; however, as previously discussed, this relationship is extremely complex.