How to Streamline Maintenance for Commercial Fleets
Learn about how Pitstop Connect can help streamline maintenance for commercial fleets
Episode 185: Commercial fleets are looking for ways to save money and increase uptime. Many of our traditional methods of performing maintenance and repairs and getting parts are not as streamlined as they could be.
How can technology help us streamline these processes?
My guest today is Shiva Bhardwaj the CEO of Pitstop Connect.
Shiva Bhardwaj is the Founder and CEO of Pitstop, a Toronto-based predictive maintenance platform for the automotive and transportation industry. Pitstop’s proprietary algorithm – a unique blend of embedded automotive domain knowledge, time-series data, AI technology, and machine learning – provides customers with the ability to gain insight from their data to save costs, reduce downtime, and recalls, and increase safety. Shiva has also been recognized as the Vaughan Entrepreneur of the Year & SEMA 35 Under 35.
Guest Website: PitstopConnect.com
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Transcript of Episode:
Jamie Irvine:
You are listening to The Heavy-Duty Parts Report. I’m your host, Jamie Irvine. And this is the show where you get expert advice about heavy-duty parts that keeps trucks and trailers on the road longer while lowering cost-per-mile.
Commercial fleets are looking for ways to save money and increase uptime. Many of our traditional methods of performing maintenance and repairs and getting parts are not as streamlined as they could be. How can technology help us to streamline these processes? My guest today is Shiva the CEO at Pitstop Connect. Shiva is the Founder and CEO at Pitstop. This is a Toronto-based predictive maintenance platform for the automotive and transportation industry. Pitstop’s proprietary algorithm is a unique blend of embedded automotive and commercial vehicle domain knowledge, time series, data, AI technology, and machine learning. And it provides customers with the ability to gain insight from their data in order to save, save money on costs, reducing downtime, recalls, and increasing the safety of the vehicle. All contributing to lowering the total cost of operation. Shiva has also been recognized as the Vaughan Entrepreneur of the Year and SEMA 35 under 35. Shiva, welcome to The Heavy-Duty Parts Report. So glad to have you here.
Shiva Bhardwaj:
Yeah. I’m glad to be here. Thanks for inviting me.
Jamie Irvine:
So how can AI technology help commercial fleet streamline their maintenance operations? It’s a pretty open- ended question, but I’d like to hear your perspective on it.
Shiva Bhardwaj:
Yeah, for sure. Well, there’s more data than ever before. And I think to really find what’s valuable in data sets, being able to use AI is a critical aspect of it. There’s easy examples like with dash cams, for example, you only need to record those moments that are most critical to teaching you about your driving behavior or to log an accident. And majority of the data is not informative or telling you of anything specific. When you look at the other data sets on the vehicle, the engines spitting out temperatures, pressures, flow rates, all of this data consistently every few seconds. There’s a lot in there that is not useful, but then there’s very important nuggets that can indicate and tell you things about the performance of the vehicle and tell you what’s going to happen in the future. And AI allows you to constantly monitor everything in real time because as a human, you don’t have that ability and time to do it.
Jamie Irvine:
Yeah, that makes a lot of sense. And when it comes to data though, I just came back from, well, you were there as well, The Technology and Maintenance Council in Orlando, and one of the conversations that we keep hearing about is how much data there is now. So how big of a problem is data overload for fleets right now?
Shiva Bhardwaj:
Yeah. Like most fleets seem to have some form of ELD or telematics embedded and vehicles are setting off fault codes of all sorts. And on top of that, then there’s a raw sensor data as well. When you’re running a fleet of a few hundred vehicles, it’s quite difficult to know, Hey, is this P102 code more important than this other code that’s been popping up? And does it mean that I should go send this truck in for service or can it keep driving on the road? There’s all these questions that a fleet managers are asking and through their experience, they’re answering it, but that might not be consistent. If you have junior people on your staff that are helping support the process, how are you going to train them and get them up to speed with the process that you’ve built through your experience? And because of this data overload, we think that AI is a clear solution to help streamline that process.
Jamie Irvine:
Right? And, and I mean, with people retiring in our industry faster and faster all the time, this problem’s only gonna become more pronounced because like you said, you’ve got all that experience walking out the door when they retire. And you have people who are trying to find their way and just haven’t had the years. I know when one of my mentors said to me, how do you get 20 years parts experience? He said, come see me in 20 years. So technology seems to be a great accelerator of this, both on the parts side and on the operations service side, to be able to get people up to speed faster. I’m curious when it comes to really deciphering which data is beneficial and which data should be actionable. Can you go into a little more description of how your system works to help fleets with that?
Shiva Bhardwaj:
Yeah, of course. So the way we’ve built our solution is we actually took data from about half a million vehicles through partnerships. So this is data of things like the temperature of the engine, pressure, RPN speed over 18 to 36 months of the trip alongside what service events have happened during this period of time. So were the brakes were placed, was there an engine issue? Was there a diesel exhaust system issue? What kind of fault codes were also present at the time that these service events were happening? When you have all that data, you end up finding what signals and patterns typically lead to certain groups of faults. And because you know how long it’s been in for service, you can equate that to what the downtime impact is for the fleet. So we have a ranking system software that provides a critical major or minor rank to any specific issue.
And it’s doing it based on looking at all that history and saying, Hey, last time this happened on these 400 assets across 10 different fleets it led to a few days of downtime or five hours of downtime. So it’s a critical risk item because you’re going to face something unexpected soon. And that’s when costs are the highest. So being able to prioritize and rank these fault codes, these alerts, is the key to making it actionable. So you then on a day to day basis only focus on the few vehicles that are at risk rather than trying to look at the whole population and hope that the driver’s communicating with you effectively as to what’s going on in the cab of the vehicle, which can be quite difficult.
Jamie Irvine:
We’re gonna take quick break. We’ll be right back. Don’t have a heavy-duty part number and need to look up a part? Go to parts.diesellaptops.com or download the app on Apple or Android to create your free account. Looking for high-quality fuel injection for heavy duty applications? Having one supplier for fuel injection allows you to better serve customers by providing them with a complete line, which increases your sales and profitability. Learn more at ambacinternational.com/aftermarket. We’re back from our break before the break, we were learning about Pitstop’s Connect AI technology and how it’s helping commercial fleets. Shiva, let’s talk about a situation where you have a fault code. Let’s get into some specifics here. So how does your system help the fleet deal with that specifically? So a fault code has come up. Let’s say the driver is a couple hundred miles away from home base, they’re on a run, walk us through how that system will work and what fleets can expect and then what they can do with that information.
Shiva Bhardwaj:
Sure. I can talk about an example that we’ve been experiencing with certain Freightliner vehicles where there’s fault codes coming up around on the intake pressure around the manifold pressure? It sometimes is accompanied by faults around the exhaust recirculation, EGR valve and system, but we’re finding that every time this fault comes up and it triggers an alert very frequently. So within a sequence of four days in a row or something of that nature, it typically leads to an EGR replacement. So that’s a clear example where the system has seen this fault appear in the past. It’s seen what the fix is, and more often than not, it’s clear that fleets have to bring the vehicle in to change the EGR. So we instantly, when this issue comes up and we start to see it trigger multiple times within a sequence, a small portion of time, we trigger it into a critical alert. So they know, Hey, this is coming up, if you don’t change the EGR, it can lead to the vehicle entering the degeneration state where it gets locked out, and then you gotta tow it in and reset the computer. That’s a prime example right there.
Jamie Irvine:
Yeah. That makes a lot of sense. And I can see how that has implications for parts, for service, for everything. Because if, you know, ahead of time, Hey, this is going to happen. And I wanted to clarify something. So this isn’t just the data from the specific fleet. This is data that you are harvesting across your entire network and providing insights to specific fleets. Is that correct?
Shiva Bhardwaj:
Yeah. We try to leverage knowledge about how the machine is operating and what solutions have been used to fix these machines.
Jamie Irvine:
Right, so then service and parts then can take advantage of that. Leverage that information to say, okay, we know an EGR needs to be replaced. So we’ve got to order the part. Now, before the truck even arrives, we’re gonna clear a bay that truck’s gonna come in, you know, at five o’clock tonight, we’re gonna get that done with the night crew and that’s back in service tomorrow morning and we avoid the breakdown and the unscheduled downtime and all of the additional costs related to that just by having that information ahead of time. Is that correct?
Shiva Bhardwaj:
That’s exactly it. Yep.
Jamie Irvine:
As someone who kind of grew up in the industry prior to telematics, prior to all of this, everything was reactive, right. Something would happen and then you would have to react to it. And that created all kinds of issues, especially when you are on tight deadlines, commitments to customers, like things like that. So getting ahead of that is an important part of managing your uptime. So let’s talk a little bit about the total cost of operation or cost per mile. Have you been able to provide your, your customers with data that has helped them to lower that total cost per mile or the total cost of operation?
Shiva Bhardwaj:
Yeah, so we we’ve been able to help customers reduce their downtime. And I think for each fleet it’s different. So it depends on what are your operation hours for that vehicle? Like when are you expecting it to perform its job? And then when is it not performing its job? So understanding those two sequences of time, and then during the periods where it’s supposed to be doing some sort of work or job and being productive, what’s causing it to stop or get stuck, is it in the service center? And if it is, for how long, and so you use a lot of that input and data to benchmark, where’s the fleet at today. And then we start to use our software and give them suggestions as to, Hey, on any given day, this is what we think you need to be doing. And we’ve shown, we’ve been able to increase uptime for these fleets by about 25%.
So reduce the amount of time it’s in service and it reduce the frequency. Sometimes we’re finding certain vehicles are going in for its PM this week, then two weeks later, a fault code pops up and the driver’s a little bit scared. So he goes in again and whereas we can bring that all together and really reduce the unnecessary repetitive visit. And that 25% can equate to up to $2,000 per year in savings. So I guess it depends on yeah, how much mileage your trucks are driving and what the cost of downtime is to your business. So it’ll differ for a utility fleet versus logistics, but that’s the way we’ve been calculating and running the analysis.
Jamie Irvine:
So that’s driving down total cost of operation because you’re reducing uptime by 25%. Like I say, that could be as much as $2,000 per vehicle. But then I was thinking about your EGR example, fuel consumption is connected to that. So just by fixing that ahead of time, you’re actually reducing cost per mile because now you don’t have a bad EGR where your system isn’t working as efficiently, burning more fuel, things like that. And that would be applicable in fuel systems, the brakes, the drive train. There was so many applications I can see for that. So it’s exciting. So who is your ideal customer, like, you know, we’ve said fleets as a very general term, but do you have owner operators using this? Do you have vocational fleets, like over the road? Like who do you normally work with on the commercial side?
Shiva Bhardwaj:
Yeah, so we we’ve been working generally in logistics space overall. So on the heavy-duty over the road, both FTL, TL type fleets, we’ve been working with utility fleets quite significantly as well, where they, they can have class eight, but all the way down to class four and pickups that are going out into kind of off-the-road scenarios as well, anywhere where these assets are key part of doing the job is where we’ve been focusing our energy and working with a number of companies. The target has been between a hundred to a thousand vehicles in that range. And that’s kind of where we think the delivery of our product is the most significant and strongest. And we plug into existing ELD solutions like the Geotab, amongst others out there. So we’re well integrated. There’s no hardware required. We take the data off systems, we fit in also your service data, and then we bring it all together and give you these insights to help you do a better job and not just you as a fleet manager, your team. So how do you streamline the communication so that everyone’s acting as you would at any given point in time.
Jamie Irvine:
You’ve been listening to The Heavy-Duty Parts Report. I’m your host, Jamie Irvine. We’ve been speaking with Shiva, the CEO of Pitstop Connect. To learn more about this awesome technology, go to Pitstopconnect.com. Shiva, thank you so much for being on The Heavy-Duty Parts Report and thank you for challenging the status quo in the trucking industry and trying to make things better for us all.
Shiva Bhardwaj:
Awesome. Appreciate it. Thank you.
