Automotive News Canada - August 2023 - 17

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Q: Data in automotive can be used for both predictive maintenance and
predictive quality, but they are quite different. What are the benefits of
predictive quality versus predictive maintenance?
Cutulenco: More people are familiar with predictive maintenance because
it has been popular in manufacturing for some time. Predictive maintenance
comes into play when manufacturers monitor activity on their equipment and
use the data to predict when machines will wear down or fail, so they can perform
maintenance ahead of time. Focusing on machine uptime and overall
equipment efficiency is important, but it doesn't help manufacturers with the
core lifeblood of their business: the parts they produce. There is a tremendous
cost to poor quality, from wasted materials and labor to brand damage and
customer churn. Investments in predictive quality can have a significant impact
on the bottom line of any plant, more so than an investment in predictive maintenance
alone.
Through advanced analytics made possible with ML and AI, predictive quality
enables us to identify anomalies in manufacturing - and do so in real time, so we
can help a manufacturer understand when defects will likely occur or determine
what is most likely contributing to a quality issue. We help them identify the root
causes of defects and address potential quality issues proactively, not after a problem
has already occurred or when a faulty part shows up at an end-of-line test station.
By focusing on predictive quality, engineering teams can make adjustments
and implement solutions before potential problems ever impact production.
Q: Why is predictive quality extra-important with the manufacturing of EVs?
Cutulenco: Again, in today's race to EV adoption, speed to market is everything.
So if an EV part producer can optimize production and ensure high quality and
first-time through rates without rework, it puts them in a better position to beat
their competition. And because manufacturers are investing in new EV lines and
plants, now is the perfect opportunity to introduce advanced digital technology.
It's much easier to do things right from the start, rather than try to revamp
lines later. For example, choosing a manufacturing execution system (MES) and
equipment that makes it easy to share and export data allows manufacturers to
gain value from predictive quality much faster, which will enable speed, productivity
and the ability to ramp up and scale production.
Q: In the highly competitive automotive world, the manufacturing process is
closely guarded. In broad terms, can you provide an example of how Acerta's
AI platform predicted or detected a malfunction and share the end result?
Cutulenco: We can't share specific details about most of our work with OEMs like
Nissan and Tier 1 parts suppliers like Dana, BorgWarner and Linamar. But you can
check out various case studies on our website (www.acerta.ai) to learn how we've
optimized production in different automotive manufacturing plants that were
facing different quality issues.
I can tell you a bit about our latest innovation, which is in alternative fuels. We're
working with Ballard Power Systems on a project that's supported by NGen AI for
Manufacturing funding. Our new technology will help Ballard shorten their factory
acceptance testing times and identify the sources of test failures in their fuel-cell
stack assemblies. This will be a multiyear project, and we've already completed
the initial proof of concept (POC) with great results. Tests that previously took
21/2 hours are running in less than 30 minutes. Ballard is excited to move forward
because our new approach will not only reduce their factory acceptance test times
by up to 80%, like we saw in the POC, but it also will enable them to deliver industry-leading
quality to their customers at much higher speed.
ABOUT THE PANELIST
Greta Cutulenco
Chief Executive Officer and Co-Founder
Acerta Analytics
Greta Cutulenco was named to a Forbes 30 Under 30 list and was named
an Industry All-Star and Canadian to Watch by Automotive News Canada.
Cutulenco is a member of the Automotive Parts Manufacturers' Association
board of directors and holds a bachelor's degree in software engineering from
the University of Waterloo.
http://www.acerta.ai

Automotive News Canada - August 2023

Table of Contents for the Digital Edition of Automotive News Canada - August 2023

Automotive News Canada - August 2023 - Intro
Automotive News Canada - August 2023 - 1
Automotive News Canada - August 2023 - 2
Automotive News Canada - August 2023 - 3
Automotive News Canada - August 2023 - 4
Automotive News Canada - August 2023 - 5
Automotive News Canada - August 2023 - 6
Automotive News Canada - August 2023 - 7
Automotive News Canada - August 2023 - 8
Automotive News Canada - August 2023 - 9
Automotive News Canada - August 2023 - 10
Automotive News Canada - August 2023 - 11
Automotive News Canada - August 2023 - 12
Automotive News Canada - August 2023 - 13
Automotive News Canada - August 2023 - 14
Automotive News Canada - August 2023 - 15
Automotive News Canada - August 2023 - 16
Automotive News Canada - August 2023 - 17
Automotive News Canada - August 2023 - 18
Automotive News Canada - August 2023 - 19
Automotive News Canada - August 2023 - 20
Automotive News Canada - August 2023 - 21
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Automotive News Canada - August 2023 - 31
Automotive News Canada - August 2023 - 32
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