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Maintenance of motor driven systems is undertaken daily, around the world, within plants, equipment and machinery. Where there are motor driven systems, there is a need for service and maintenance. Whether contracted out, or fulfilled in-house, the collective market value for these services runs into several billions of dollars, arguably even dwarfing the core equipment markets that it serves.
The methods for maintaining a typical motor drive system are established, and generally involve manual inspections, measurements and monitoring. Yet it’s fair to say that, as a result, the vast majority of service and maintenance work carried out today is entirely reactive in its nature. A fault occurs on a production line, and a team is sent out to fix the problem, or solve the issue which caused it.
This is changing, however, as emerging technologies begin to offer a far more proactive and potentially more cost-effective solution. By using sensors to monitor motor activity like vibration and temperature over time, and subsequently analyse and logically present that data, the user is alerted to any potential issues before they become a major problem.
Improvements in the price-performance ratio of sensing technology, such as MEMS devices, is placing the cost for such systems in a bracket where mass adoption becomes viable. Additionally, the supporting technology – e.g. software, analytical tools and networking – is also maturing, bringing with it renewed clarity, accessibility and usability. Businesses are now beginning to see opportunity, as opposed to yet another swathe of ‘big data’ to wrestle with.
In systems involving variable speed drives, the potential grows even further. Many modern drive systems incorporate the relevant sensing technology within the drive itself, and there is huge potential for drive manufacturers to lead the way in this area of predictive maintenance. At the moment, drives do not tend to use their internal sensors for predictive maintenance, but this is likely to change rapidly. Drives manufacturers that don’t recognise the potential for using drives for predictive maintenance risk being left behind. In the near future, sensors will also be put inside some electric motors, thus enabling the motor to communicate with the drive and raise an alarm if excessive vibration is recorded, for example.
Yet this is not a one size fits all solution. In a lot of motor applications, particularly those utilising smaller motors, there simply isn’t the business case to justify installing sensors at every touchpoint. It is often cheaper to simply swap out the failing motor with a new one. If, however, a large motor is used in a critical application like water pumping or mining then predictive maintenance can provide a very quick return on investment.
Meanwhile, existing smart sensor companies should look to mechanical systems as an important area for future growth. Mechanical systems are complex and smart sensor companies will find that it’s here that the sensor comes into its own. For example, when bearings fail in a gearbox, it’s very tough to detect and you need highly sensitive sensors to differentiate between the noise being given out by the failed bearing, and the noise made by everything else. Mechanical systems are also often the more expensive part of the system, and are often application specific. They can’t just be replaced. And this makes them an exciting market for predictive maintenance.
Predictive maintenance has yet to achieve its potential in the area of motor driven systems, but this will change rapidly. A quick look at some other industry sectors shows us how. One example is the China Southern Power Grid, the second largest electricity company in China, which has recently adopted a predictive maintenance software solution from ABB. This ABB predictive maintenance package tracks and analyses real-time data about the performance of critical power assets such as transformers to forecast asset renewal and continuity needs.
Another example can be found in the automotive sector where Bosch offers a smart predictive diagnostics package which prevents vehicle breakdowns. The Bosch solution is used mainly by OEMs and fleet operators for both road and off-highway vehicles. The software uses in-vehicle sensors to collect data which it analyses to reliably predict both system and component failures, optimizing vehicle availability and allowing users to determine the latest point at which unplanned maintenance is going to be needed, so that it can be combined with planned maintenance visits – reducing the number of maintenance stops to a minimum.
Ultimately, in this era of growing environmental awareness (and environmental legislation), predictive maintenance is going to be a vital part of the move toward a low-waste society.
Our report, Predictive Maintenance in Motor Driven Systems, aims to shed light on areas where plant and machinery operators can benefit most from implementing these systems, as well as highlighting opportunities for drive, motor and sensor manufacturers to add differentiation and value to their portfolios.
The research has been produced at a time when the industry is at an early and transformative stage. It will quantify the key aspects of the motor-driven system market, as well as forecast where disruption will take place and which company types will be most affected.
The topic of predictive maintenance is a broad one. By focusing on the motor-driven segment of the market, we will offer targeted insight that is both useful and actionable.
If you’d like to learn more about predictive maintenance, feel free to get in touch with our CEO Adrian Lloyd directly for a 1-1 briefing: Adrian.Lloyd@interactanalysis.com