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How predictive maintenance technology helps public transport companies achieve zero downtime

by uma

 

By Nuno Mendes, Head of Product at Stratio

Many public transport fleet operators are trying to reduce downtime and extend the life cycle of their vehicle components in the face of rising fuel costs and disrupted supply chain/shortages of materials. The strategies adopted have varied from introducing express services to switching to shorter driver journeys, but have continuously failed to identify downtime and vehicle breakdowns as one of the prevalent causes of revenue loss. 

Vehicle breakdowns have always been an issue for public transport services looking to offer a reliable service to passengers. The steep decline in the number of passengers caused by the national lockdowns of the past two years has somewhat worsened the position of public transport companies, who now find themselves facing the challenge of making urban buses an attractive choice again. For this reason, the Welsh local government in the UK has recently released a new whitepaper detailing its plans to improve the efficiency of public transport journeys and deliver the best possible service to customers. However, a lack of consideration for improving vehicle downtime and reducing maintenance costs could be a key sticking point for the whitepaper vision.

Reactive actions simply not enough

Vehicle breakdowns are a cause for concern when it comes to public transportation services for a number of reasons. From a financial standpoint, transport companies need to consider the higher cost of emergency repairs, which often entail recalling a vehicle off the road and paying for parts that need to be delivered at short notice, which can rack up a substantial workshop bill. From an image perspective, downtime also causes the type of service disruptions that, in the long term, undermine the passengers’ confidence in the reliability of a bus route, or even the entire service network. This, in turn, impacts revenue generation, as customers are less incentivised to use public transport services they deem inefficient. The result is a ripple effect of revenue loss and increased spending, which ultimately affects transport operators’ bottom line.

To reduce downtime, transport providers have tried a number of different strategies including planned downtime and regular service check-ups, in a concerted effort to substantially minimise the impact of vehicle breakdowns. This has often resulted in muted improvements, falling short of the zero downtime outcomes that many were looking to achieve. 

Technology is key to solving the downtime conundrum

The issue of downtime caused by vehicle breakdowns generally stems from the company’s fleet maintenance department lacking the tools to detect and deal with the issue proactively. This is where the use of next-generation technology can help not only to minimise the frequency of these costly breakdowns, but to also eliminate them completely over time. Technological solutions such as Artificial Intelligence (AI) powered predictive maintenance can help companies monitor the health and status of each vehicle component in real time, offering actionable intelligence to plan maintenance operations. This intelligence can be used by public transport companies to monitor from simple parameters such as fuel levels or rate of consumption of components, to the more complex State of Health of major vehicle components, enabling them to act accordingly and in a timely manner, addressing specific issues before the vehicles hit the road. 

A good example of this is global public transport provider Go-Ahead Ireland adopting Stratio’s real-time predictive fleet maintenance in an effort to minimise service disruptions and prevent breakdowns. The public transport company is reported to have extended the service to its entire fleet and expect to reduce its vehicle breakdowns by over 57% in the next three years. 

The thing that makes AI predictive maintenance tools effective at reducing vehicle breakdowns is the capability to turn vehicle data into useful intelligence that can be used to inform and optimise maintenance operations. This plethora of readily available data points on vehicle conditions are collected and analysed by the AI platform, which turns them into real-time actionable insights that allow transport companies to predict and proactively deal with potential vehicle breakdowns and, as a result, completely eliminate the issue of unexpected downtime.

When it comes to effectively managing public transport fleets and avoiding costly breakdown incidents, next generation technology is integral to helping transport companies to reduce the frequency of preventive checks and plan the wear rate of components dynamically, rather than relying on more approximative mileage-based estimates. This ultimately will help companies within the public transport industry to not only offer a more reliable service to passengers, but to save money and resources too.

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