A number of companies in the maritime sector have explored remote telemetry and the potential of combining augmented reality (AR) and acoustics. While initial studies were promising, they did not get past the conceptual stage. With increasing interest in autonomous shipping, remote diagnostics of marine propulsion systems is a key mechanism required to ensure safety. This is a field which demands considerably more research and development.
It starts with research
At KP Acoustics, we wholeheartedly know the importance of seeing research topics like this one, right through to their full potential. Acoustic data from machinery, both in the maritime sector, and other sectors such as metalworking, could give huge insight into equipment health, performance and lifespan.
We’ve worked on machine monitoring projects before and know first-hand how this data can save businesses money, time and materials. So, what’s stopping acoustic data from being a widespread decision-making tool in industry?
Within the manufacturing industry, predictive maintenance is a well-established concept, dating back to the 1990’s. It has a proven track record of minimising unnecessary machine downtime and saving businesses money in the long run. The methods of predictive maintenance have varied widely, including visual inspection, thermal imaging, ultrasonic analysis, vibration analysis and acoustic emission, to name a few.
As manufacturing technologies have become more complexed, so too have the maintenance tasks, presenting new challenges for researchers, engineers and scientists. These challenges have been met through research and development of new technologies and methods of maintenance.
Some of these methods currently involve installing intricate sensor systems which are placed on the system in question. Although some of these monitoring methods have been slow to catch on in industry, much of the reason for this can be attributed to the high cost of sensors along with the high probability of needing to replace them in time due to damage.
Of course, acoustic emissions are the ideal data source for near proximity data acquisition. A wide range of acoustic parameters can be logged to establish normal baseline levels of optimal equipment. If equipment acoustics deviate outside of set thresholds, operators can be notified in real time.
Research in this field must validate the return on investment of acoustics-led remote monitoring, and also explore new ways to reduce cost barriers before this kind of monitoring becomes the norm. That said, the early adopters will garner the benefit of having more time with this technology, to start reaping the financial benefits sooner and iron out any integration issues ahead of the curve.
There is also significant potential to blend AI and human expertise using remote simulations to identify and solve problems in remote operations before they become critical. Research will also need to identify how this monitoring system could be integrated within the smart manufacturing environment that is being driven by Industry 4.0.