The most pressing question for fleet managers is: “How do I keep my vehicles on the road, in tip-top condition, while holding my TCO down to the minimum, without compromising on maintenance, safety, efficiency and profitability?”
The short answer is “Look to Predictive VHM”: The long answer, which explains exactly what we mean by Predictive VHM and its implications, is the subject of this blog.
The thousands of systems in each vehicle all need constant monitoring, adjusting, maintaining, replacing and more to keep the vehicle running productively. Just one vehicle being out of service for even a single day can cost companies between $448 to $760 per day! That’s without considering the enormous knock-on effect throughout the entire enterprise. Not just late delivery or pick-up – or NO delivery or pickup – but a loss of reputation, the potentially harmful effect on the customer’s business, the loss of earnings, a subsequent loss of customers…the list goes on.
According to American Trucking Associations, trucks move nearly 75 percent of the nation’s freight by weight, bringing in more than $732 billion in gross freight revenues in 2020 alone. More than 38 million commercial trucks are registered translating into 14.4 percent of all registered vehicles.
Fleet managers are thus highly challenged to keep ahead of the maintenance game. They need to know how to keep the wheels rolling at the lowest possible cost, particularly in this era of far-reaching developments in the motor industry, with the advent of electric and autonomous vehicles.
Vehicle performance monitoring is nothing new: it’s been around for more 180 years! Tachographs were originally introduced for trains as a way to record performance irregularities as far back as 1844. In ancient (pre-digital) times, commercial vehicles, busses and heavy-duty vehicles, were fitted with a mechanical Tachograph, an early version of telematics. A circular card sealed in a tamperproof recording unit bolted into the cab. The cards were removed by the transport manager at the end of the day’s activities and sent for analysis, to decipher the graphs and tick marks on the card to gain a picture of the vehicle’s – and more specifically – the driver’s behavior. Available data covered speed, distance travelled, fuel consumption and other daily performance characteristics. While Tachographs are still in use today – although rather more sophisticated with digital capabilities – they are more concerned with speed, distance, and driver activity than actual maintenance.
The TCO of a vehicle is the sum of all the costs associated with acquiring and running it over its fleet life. TCO covers the complete range of expenditure on a vehicle, including depreciation, interest payments on loans or leases, taxes, service and maintenance, insurance, fuel and more.
The AAA (Automobile Association of America) estimates that the annual cost of keeping a half-ton pickup on the road will reach upwards of $10,000. This cost will naturally vary depending on the size of the vehicle, its annual distance travelled, age, payloads, and dozens of other factors.
The costliest elements of fleet ownership today are fuel and maintenance. Fuel accounts for more than 30 percent of the TCO in commercial fleets. Preventative maintenance (PM) costs have continued to rise between 3-5% every year since the end of 2017 when PM stood at $66.05/vehicle/month. By the end of 2018, PM per vehicle stood at an average of $75.32/month. Today it costs $115/per month per vehicle and is expected to increase at the same rate during 2022.
PM refers to the regularly performed tasks on a vehicle: oil changes, tire rotations, topping off fluids, changing the brakes…all vital routine tasks very similar in concept to what we do with our private vehicles and performed according to a predetermined set schedule and checklist.
Running a fleet is becoming increasingly complex. Vehicles are more sophisticated, and traditional telematics, based on limited data and preconfigured error codes designed for PM, may no longer be up to the task.
Predictive Maintenance (PdM) on the other hand, simply means being able to predict a technical fault in the vehicle in advance. It differs from preventive maintenance because it relies on the actual condition of equipment or vehicle, rather than average or expected life statistics to plan when maintenance will be required.
Advanced machine learning systems tap into the full array of data uploaded by a connected vehicle, to a server equipped with big-data analytics and AI-based detection algorithms reflecting the performance of individual parts and systems in the vehicle, helping fleet managers to better predict when problems will occur. It empowers them to ensure that a vehicle requiring maintenance is only taken off the road right before imminent failure. Thus significantly reducing the total downtime and outlay spent maintaining equipment.
More than 15 years’ worth of data gathered from actual vehicle operations and combined with advanced AI and deep learning solutions, enable Questar to put fleet managers on the road to significantly lowering their TCO. Key factors include fuel efficiency, insurance and probably the most important element, improved driver performance.
Better driving habits result in less mechanical wear, while better drivers improve the fleet’s safety record, eventually resulting in lower insurance costs. Good driving habits – accelerating and braking smoothly and gently, instead of fast and hard – can save as much as 10% in fuel economy. And better drivers are more attuned to ensuring correct tire pressures which have a major impact on achieving optimal fuel efficiency.
Running with the correct air pressure means lower rolling resistance and less energy needed to propel the vehicle. According to the U.S. Environmental Protection Agency, under-inflated tires can reduce fuel economy by about .2% for every 1 psi below the recommended air pressure. So if your tires are even 5 PSI under-inflated, you are losing at least 1% in fuel economy. Predictive Maintenance using data from tire sensors and telemetry data ensures that this area is consistently monitored.
Looking just a little farther to the future: prediction in VHM will become super critical with autonomous vehicles.
Everyone today is talking about how to make sure autonomous vehicles drive safely, not crash into each other, start and stop when needed. But no one is talking about how these vehicles will be maintained. Since there won’t be a driver looking for Diagnostic Trouble Codes (DTCs) in the vehicle, advanced VHM prediction capabilities are a must to create “autonomous maintenance”.
With connectivity rapidly becoming ubiquitous in vehicles, data about nearly every system can be uploaded, and analyzed to ensure vehicle health, maximum safety, regulatory compliance, performance optimization and much more.
Our AI-based platform delivers cutting edge telematics and data analytics solutions to our customers – automakers, Tier 1 suppliers, and fleets – providing an accurate prognosis of future vehicle health events before they occur.
Already today, the platform enables vehicle fleets to significantly reduce their operating and maintenance costs and enables automakers to reduce the cost of vehicle development, improve vehicle quality, lower warranty claims costs, and more. These deep insights will change the way fleets are managed, optimize expenditure, increase operational efficiency and safety with a clear and aggressive ROI.
Questar’s solutions will help users unlock the value of vehicle data while enabling automakers and their customers to offer advanced connected services and create new business models that can increase their revenue. The more data generated, the greater the need for more sophisticated systems and solutions to be able to make sense of the data and use it to maximum benefit. Contact Questar with any questions or concerns you may have in this area. We invite you to take advantage of our experience, advanced knowledge and expertise.