february2023 - 24

" [Intermittent engine- or tire-related DTCs
might not] mean anything for you to act on in the
short term, but could escalate and get worse over
time, " he warned.
Pitstop focuses on the DTCs that first indicate
immediate danger, and then what the data says
will likely lead to problems, which he demonstrated
on the platform with real-world data.
" Based on the next 30 days, here are 70 vehicles
that we've got to probably pay more attention to
and within those, there's some that have more
potential to break down versus others, and we
rank those in order, " he said.
Suggestions are then given, such as get to a shop
right away or ask for driver input, who will have
a much better sense of what's happening with the
vehicle in real time.
And while a five-day weather forecast ends up
being about 80% accurate, Pitstop claims 94%
accuracy for issues in general, and nearly 100%
with " very rare, critical issues, " Bhardwaj said.
Uptake Fleet, which had 70% detection accuracy
on all failure modes previously, used a new
configuration to improve to 90% detection accuracy
for the cylinder issue to save that large fleet
so much money.
Data overload
" With any data-based solution, there's a lot of
data you need to filter out, " advised Jean-Phillipe
Bertrand, operations director at Isaac Instruments,
a telematics and ELD provider for the U.S. and
Canada. He likened taking in all the raw data to
drinking from a fire hydrant. "
Bertrand said to keep from being flooded with
non-value data, a fleet should highlight only the
data most important to their operations, especially
if they are new to the technology.
A fleet should do this through KPI benchmarking
and identifying the biggest cost center, and
then choosing three or four specific areas and
relevant fault codes to reduce cost, recommended
Melanie Simard, Isaac's director of compliance,
client service, and technical support.
» The SureTrack feature of Mitchell 1's
ProDemand allows users to narrow down the
root cause of a fault based on historical data.
Mitchell 1
" This will establish your baseline when starting
with a new solution, " Simard said. Various fleets
might need to focus on tires one year and aftertreatment
or fuel filters the next, she added, recalling
her previous 20 years of fleet experience in Canada.
Once these are picked, a fleet should automate
related reports, such as historical costs on costly
components, and send those to key managers.
Database size matters
Predicting future downtime is
easier said than done. Because
data and probability are involved,
sample sizes matter with a trustworthy
predictive solution. The
more historical data that's available
to analyze, the more accurate
the prediction will become.
" You've got to have a certain
amount of history to train the system
so that it kind of understands
what the trends are, " explained
Ben Johnson, Mitchell 1 director
of product management.
Because of this, at Mitchell 1,
" there's nothing commercially
available, but we are evaluating
who to partner with and how to
bring to bear more predictive
analytics, " Johnson noted.
Even so, Mitchell 1, which leverages
repair information from its
ProDemand platform, has more
than enough to data to make
highly accurate predictions when
a solution is commercialized.
" In our data pool, we've got around
a billion repair orders (and it
grows by about 40 to 50 million a
year) that we derive value from, "
said Johnson, who added that
the company invested " a ton of
money " into an artificial intelligence
that focuses on transportation.
Consumer vehicles, along with
lighter commercial vehicles up to
Sprinter vans to Ford F-350s, have
by far the most data collected.
" On the light vehicle side, you
give me any year, make, and
model and ask me when something's
gonna break, and I can
tell you, " Johnson asserted.
There is still work to be done
in heavy-duty, though.
" It's just a matter of getting
the amount of raw data to run
through an AI system so that
we know that we can trust
the results, " he said. Another
major challenge for predicting
heavy-duty more accurately is
the variety of duty cycles and
regions. The same truck with the
same engine will wear differently
based on regional or longhaul,
as well as in the mountains
versus mostly flat terrain.
Even with that confidence in lightduty,
he said Mitchell 1's insights are
used more reactively when a vehicle
comes into the shop. If, hypothetically,
a pickup comes in with a mass
airflow sensor trouble code, and the
technician also receives a certain
power supply DTC, then the software
can narrow the problem down.
On a virtual call, Johnson brought
up the ProDemand light-vehicle
tool SureTrack, and selected a 2016
6L Chevy Silverado, which had
138,000 different repair orders.
Johnson demonstrated how a
user can obtain data on the most
frequent trouble codes, replacement
parts, and symptoms.
After a few clicks he found for a
certain DTC that a defective mass
airflow sensor was the most prevalent
culprit. Based on that, Johnson
said a technician can validate and
prove if that is the real root cause.
" We can look to see what the mileage
is that this sensor typically fails
at, and it looks like around 100,000
miles is the peak of it, " Johnson said
while diving into the data. " So, if
you're dealing with a vehicle with
only 40,000 miles, you might look
at connectors or something like
that, because the sensor is really
not in its normal failure range. "
In this low-level use of predictive
data, the human element
is still very critical.
" We never ever say, 'Because of this
code, replace that part.' You do still
need the human to pop the hood, "
Johnson said. " You need the human
to say, 'Yeah, the AI didn't see that
mice got in here and chewed up
the wiring to this mass airflow. "
Johnson also stressed, as far as
Mitchell is concerned, AI and predictive
tools " will never replace the
human and we don't intend to. "
Instead, these should be looked at
as the ability to help narrow down a
location from a global perspective to
a country-, state-, and county-level.
" We might get them into the right
house, " he reasoned, " but even
if we can't get them there, we've
done so much for them instead
of making them try to navigate
that world and figure it out. " -JH
24 Fleet Maintenance | February 2023
february2023

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