5 Factors Impacting the Future of Predictive Maintenance 

Predictive maintenance is a newer phenomenon. Some question if it’s any different from preventive maintenance, as both have the ultimate goal of preventing unscheduled problems and repairs. The answer is yes. Predictive maintenance takes preventing issues one step further, utilizing data and information specific to a fleet and specific vehicles. 

Rather than simply performing truck maintenance based on time and assumptions (an oil change every 5,000 miles, for example), predictive maintenance takes data to say when a specific vehicle should have maintenance performed based on how it’s actually used and information gathered from other vehicles doing the same route, in the same region, etc.

So, what does the future hold for the crystal ball of truck fleet maintenance?

1. Further Integration in the Future 

Fleets are already moving from reactive to predictive maintenance and OEMs are participating in predictive maintenance by integrating telematics into the vehicle to better understand utilization and the need for maintenance. 

“OEMs and third-party telematics service providers are creating predictive maintenance programs and leveraging the detailed diagnostic data about the vehicle to send maintenance alerts and direct vehicle owners to OEM or other third-party maintenance providers for servicing,” said Frank Schneider, director of product management for Software as a Service (Saas) at CalAmp. “Telematics and automated intelligence will be integrated into the vehicle and maintenance alerts will be automatically sent to the owner. Custom programming using telematics technology is essentially using machine learning to capture unique insights to better understand the performance and utilization of a vehicle and using those insights to make design and engineering improvements.”

2. More Data Precision  

Fleet management software, including vehicle diagnostics, continues to evolve and help to progress the industry rapidly. 

“Real-time feedback already helps fleet maintenance managers make smarter decisions on which vehicles to service and when. In the future, we’ll continue to see real-time feedback and alerts become even more precise and predictive. As machines share information autonomously, actionable data results can help businesses transition away from traditional reactive operations and respond more quickly, becoming more productive and delivering a higher level of service to customers. The connected vehicle is already revolutionizing how companies operate in the field and is giving enterprises the key to unlocking a lot of potential that was previously untapped. Diagnostic alerts are a big part of this new age of the connected vehicle. For example, using diagnostic trouble codes (DTCs) directly from the vehicle’s engine control module, GPS vehicle tracking solutions can alert a fleet manager of maintenance issues in real time. Thus, major downtime or costly repairs can be avoided by resolving problems early. We expect that technology such as DTCs will continue to help progress connected vehicles forward, including the road toward self-driving vehicles,” said Chris Ransom, director of solutions engineering at Verizon Connect.    

Unfortunately, there is no total crystal ball into truck fleet maintenance yet. 

“There's no solution out there that's gonna say: 100% in every case that this is a failure and that you need to fix. But it's pretty good right now. You can get a high percentage of accuracy saying this specific vehicle is likely going to have an issue. So as a number, these programs get more data, they get more outcomes, and they can continue to improve their models,” said Scott Sutarik, associate VP of commercial vehicle solutions for Geotab. “We’re in early days of this. We have the first phase done. We went from the trucks broken down let's get it towed to using telematics to say, ‘Hey, you have a high-severity fault code, we think that this will fail in the future too.’ The next step, which is just starting to come out is using additional data to provide greater insights. The more data you get, the more outcomes you have, the better you can train your models, which will continue to increase the overall number of catches and benefit.”

3. Continue to Reveal Benefits

Technology will continue to promote efficiencies in asset maintenance management. 

“Cloud-based software and machine learning will expand capabilities and deliver insights we’ve yet to attain. These powerful tools are in the infancy stage and developers’ abilities to solve complex problems will further reduce downtime and make managing assets an easier process,” said Tony Summerville, founder & CEO of Fleetio. “I could even see it being regulated/required one day to protect drivers and promote driver safety.”

4. More Actionable Insights 

With the advent of more OEM onboard telematics solutions and more advanced aftermarket devices, the available engine data set is constantly growing.

“There are two key aspects to such a solution and there are significant changes and enhancements in progress in both areas. The first area is increasing the vehicle engine and diagnostic data set available to analyze and act on. OEMs, in particular, have the power of exposing more of this data to their customers, with higher reliability and without the need for reverse engineering, and they are incentivized to do so as a differentiator of their solution. The second area relates to technologies and tools needed to analyze complex data sets, detect patterns, and translate to actionable insights for end customers. This is where the application of advanced analytics and machine learning is moving at a fast pace, not unlike many other similar technology segments,” said Reza Hemmati, VP of product management for Spireon. 

The change here would be to further automate the process and rely on prescriptive data/insights versus performing arbitrary costly an ineffective periodic maintenance.

“There will be less waste associated with a fleet’s maintenance program, but predictive maintenance will also require fleet management and fleet maintenance software to make it easier for fleet managers to track of predictive maintenance tasks while making the users’ day-to-day operations easier,” said Marco Encinas, product manager global platforms for Teletrac Navman. “Also, the condition monitoring tools will become easier to use so it doesn’t take specialized training for employees to use them.”

5. Continued Improvement

Overall, similar to any new solution or concept, time will tell and work is required to educate and improve data.

“We see this as a significant step up as the solutions improve: hardware, software, data science, ecosystem data on repair costs, etc. We also see an evolution from ‘tell me something I don't know’ to ‘don't just tell me, fix it for me.’ While this is a tall order, an example of this would be finding the best repair/maintenance shop for the job, scheduling the work around periods of lower utilization for drivers, calendaring it, providing driving directions, and also extract deals and discounts,” said Ananth Rani, co-founder and CEO of Azuga, Inc.

Are you currently looking to add a predictive maintenance program to your fleet, or do you currently utilize predictive maintenance solutions? How is it working out? E-mail me, let’s chat!

Lauren Fletcher
lauren.fletcher@bobit.com