Predictive maintenance is not a new concept. Other industries and organisations, such as commercial airlines and armed forces, have seen great success with it:
- Airlines monitor the condition of their fleet’s individual components, making it easy for staff to troubleshoot issues and circumventing the need for costly manual inspections. Reports suggest that this approach can cut an airline’s maintenance budget by up to 40%.
- The Belgian navy used predictive maintenance to maintain complex equipment as a solution to the challenge created by personnel and funding cuts. This increased their mean time between maintenance by 60% and brought savings of €1.5 million a year.
Why predictive maintenance?
Predictive maintenance is essentially about prevention rather than cure. At a basic level, it is performed by analysing the data obtained through asset components and planning maintenance activity proactively instead of reactively.
Predictive maintenance has several advantages over reactive or schedule-based maintenance.
Firstly, it significantly decreases your organisation’s chances of having a breakdown in the middle of a service and causing commuter frustration, timetable disruption and negative media attention. (We’ve all seen angry tweets and Facebook posts from stranded passengers.) Don’t wait until something breaks before you fix it – keep it in good shape so it doesn’t break or replace it before it does.
You will also be able to increase the mean time between failures on your assets. Your system should have pattern recognition and machine learning algorithms to process and analyse the data reported by your assets’ telematics units. This can then be used to anticipate when maintenance is due to proactively keep components in a state of good repair, making failures rarer.
Predictive maintenance is also less time-consuming for staff, which saves your organisation money. With reactive or schedule-based maintenance, a large part of maintenance costs stems from the need for employees to manually inspect assets and find the cause of breakdown or failure – a time-consuming process. Predictive maintenance reduces this inefficiency.
Last but not least, predictive maintenance helps to decrease workplace accidents. Similar to industries such as oil and gas, when public transport assets break down they pose a risk to your staff. A predictive maintenance approach means you’re keeping equipment in good condition and thereby preventing accidents caused by asset failure.
The end result
Not only will you provide a safer workplace for your staff and a better service for your passengers, you will also end up saving costs in several ways. Predictive maintenance helps you use your maintenance workforce more efficiently, reduces the frequency of asset failure and increases your assets’ useful life by keeping them in a state of good repair. If your current solution is not meeting your needs and helping you perform predictive maintenance, you may be interested in reviewing our Enterprise Asset Management system.