FUEL EFFICIENCY SOLUTIONS
• Optimized idle and
SAFETY AND COMPLIANCE
• Speed governing
• Seatbelt-dependent start
• Distracted driver prevention
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32 Fleet Maintenance | June 2018
STORAGE ANALYTICS PRESCRIPTION
A truck’s fuel consumption can be
monitored and correlated with load
weight, terrain and weather. If the situation
is degrading, the truck can be
fl agged for service.
Readouts of engine and transmission
data will detect faults before they
become catastrophes. Th e soft ware will
continuously monitor for “not to exceed”
values, and trends to alert the driver and
dispatch of the issue. Decisions can be
made in real-time with considerations to
the vehicle load, customer, distance from
service stop and location of replacement
units or parts.
Soft ware analyzes this data with
pre-programmed parameters. If and
when the data registers outside of these
parameters, the soft ware program notifi
es the fl eet of an issue. Th e fl eet can
then make an educated decision about
taking the unit out of service at a particular
time based on this information.
Th e soft ware can be programmed
to monitor driver behavior. On-board
systems can sense driver impairment
for things like fatigue or substance use.
of data usage
Th e adoption and use of data can be categorized
into three stages of transformation.
Th ose stages are: access to vehicle
data, use of real-time diagnostics and
a higher level of comprehensive data
Stage 1: Access to the data
Vehicle system and component sensors
provide data readouts, which are accessible
with a scan tool or other diagnostic
tooling. Dependent on the maintenance
operation, like the case of a local Kenworth
dealer, soft ware management platforms
are available to assess this data in the
shop, and connect to other programs.
For example, Kenworth launched a cloudbased
Service Relationship Managment
(SRM) platform, powered through Decisiv,
giving the technician access to all the
possible relevant information.
Th e SRM platform provides detailed
information on vehicle specs, parts
catalogs, service bulletins, warranty
and repair history, etc. Th is information
can help the fl eet diagnose, estimate and
complete service work more effi ciently.
Stage 2: Access to realtime
Kenworth has also taken the data
collection technology to the next stage
with the ability to access and monitor
real-time vehicle data through the
TruckTech+ Remote Diagnostics platform
available on the company’s heavy
“Th e technician may be able to skip
those diagnostic tests and start work
immediately on solutions, by relying
instead on real-time diagnostic data
from the truck’s engine control module,”
Mark Wasilko, Decisiv’s vice president
of marketing services, says. Wasilko
advises real-time diagnostic information
from a variety of systems and sources
can help fl eets make better decisions.
It works by the vehicle generating data,
with the data then sent to the cloud for
storage. In the cloud, this data is accessible
by the fl eet, and the dealer or OEM
and can be monitored in real-time. Th is
gives the fl eet a jump on dealing with
serious deterioration or defects.
Th is technology is already in use
at Central Oregon Trucking Co. in
Redmond, Oregon, contributing to
on-time delivery and optimized maintenance
schedules. Real-time vehicle
diagnostics information is transmitted
24/7 from the fl eet’s maintenance facility
to the local Kenworth dealer. Th e fl eet
can also view this information through
the Paccar Solutions web portal in their
shop to confi rm how and when a specifi c
issue will be addressed.
“It allows us to complete shipments, and
schedule the servicing for when the driver
returns to home base, or somewhere along
the way when the driver is off -duty,” says
Josh Laughlin, maintenance specialist for
Central Oregon Trucking Co.
Th is process of real-time data stream
review and analysis can help save
money and improve customer service.
Adding GPS location capabilities, a fl eet
can determine the severity of the issue,
review the location of available dealers
on the truck’s route and the delivery
schedule of the truck, to make an
informed decision to fi x it immediately,
when it gets back to the shop or during
future scheduled maintenance.
Decisions made by the fl eet or dealer
is based on data from a variety of
systems and sources and is critical to the
decision-making process, Wasilko says.
Only then can the dealer make optimal
business decisions for their customers.
Good customer service leads to
stickier customers, potentially more
revenue and vehicle uptime.
Stage 3: Higher level of
comprehensive data analysis
Th e next step to using data for maintenance
involves accessing and using Big
Data. Big Data may seem like an intimidating
term, but it really refers to the
combination of all the available data
that has been collected.
Big Data can be better described
through the four “V’s:” volume, velocity,
variety and veracity.
Volume: Th e best driver might scan
his or her oil temperature once every
couple of minutes. Vehicle sensors can
scan the system every second. All of
this information is recorded.
Velocity: Th e data sources are working
much faster than ever before.
Variety: All the data has always
been available. Th e diff erence with
Big Data is that it is all together in
one place. Now we can correlate
weather and cranking systems
or changes in altitude with brake
repair, for example.
Veracity: dealing with the uncertainty
of the data by cross-checking
it with other data and using advanced
statistics to ferret out the truth.
Th e industry is in the early stages of
this adoption currently, with soft ware
having the ability to provide more
insights to the performance of the vehicle
and decision-making process.
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Block diagram for high tech maintenance
• Wireless sensors
• Wired sensors
• Predictive maintenance
data feeds (offline upload)
• Repair data from CMMS
• PM tickets
• Operational data
• Outside data sources
• OEM insight
• Local machine
• Local maintenance
• Document management
• AI and ML
• Compliance and laws
• Decision making
• Work orders for action
Data can be structured or unstructured.
Illustration provided by J. Levitt