Automotive News Canada - August 2023 - 16

DATA WILL DRIVE SUCCESS
IN EV MANUFACTURING
It's easy to feel overwhelmed by the rapid influx of new
data-driven technologies being adopted by electric-vehicle
manufacturers. From machine learning and artificial
intelligence to predictive maintenance and predictive
quality, it's clear that the industry is undergoing a rapid
transformation. How will these new technologies impact
the industry? And how will these data-centric technologies
help separate winners from losers in the years
ahead? For some clarity, Automotive News Canada spoke
with Greta Cutulenco, the chief executive officer and
co-founder of Acerta Analytics. The company develops
software solutions, driven by machine learning and artificial
intelligence, that translate complex manufacturing
data into actionable insights.
Q: Many technology companies from other disciplines
are trying to cross into the electric-vehicle (EV) space.
Acerta has been solely focused on the auto sector...
How does that differentiate you from newcomers that are trying to get
into EVs?
Greta Cutulenco: EV manufacturing is an attractive market sector for technology
companies that customarily focus on other verticals - and especially so
for companies that typically serve electronics manufacturers, since the number
of electronics required in an EV is growing significantly. However, we have a
couple of big advantages over them.
One, we have a proven track record of successful and scalable implementations
within the automotive manufacturing environment. Our deep experience
with the unique needs and realities of these facilities positions us well for a
transition into EV component manufacturing - far more so than newcomers
that are trying to enter the EV market from other industries outside automotive.
We've built a solid foundation upon which we can dive into fuel cell, battery
and electronics production for EVs.
Two, our focus on predictive quality is unique because we operationalize the
use of machine learning (ML) and artificial intelligence (AI) in high-volume production
- and it's scalable globally. This is key in the automotive industry and
will play a huge part in the growing EV transition. It's also something that other
newcomers will struggle with.
Q: Disruption in the automotive world is happening right before our eyes,
and Industry 4.0 is upon us. Do you think this level of change is creating
opportunities for companies like Acerta, a relatively new Canadian
startup, to carve out a bigger niche in the auto sector?
Cutulenco: Absolutely. Many manufacturing companies have already put
Industry 4.0 infrastructure in place, which allows them to collect and generate
more data. But many of them aren't actually using their data to its full
extent. Manufacturers are struggling to derive actionable insights and value
from the data that is being collected, which has provided a tremendous
There is a huge opportunity for
Canada to be a leader in EV and battery
production on the global stage, but we
need a solid strategy to get there as full
EV adoption ramps up...
Greta Cutulenco, CEO at Acerta Analytics
opportunity for companies like Acerta. By focusing
on use cases that directly impact production quality,
we help automotive manufacturers and part suppliers
operationalize their manufacturing data to get real
value from it, such as rework and scrap reduction or
general staff productivity. And because predictive quality
still is a niche category in the industry, none of the
big incumbents have become the de facto standard
yet, so it's the perfect place for us to win in the market.
Q: There is so much new auto sector investment
coming to Ontario, and billions of dollars are being
directed toward EV and battery production. What
effect do you think that will have on Canada's importance
within the global automotive industry?
Cutulenco: There is a huge opportunity for Canada to be
a leader in EV and battery production on the global stage,
but we need a solid strategy to get there as full EV adoption
ramps up during the next few years. It is encouraging to see several OEMs
already commit to new EV sites in Ontario. Personally, I'd like to see more investment
from Ontario to support the Tier 1 and 2 suppliers, which would further
help position the entire industry more strongly in the EV space. Additionally,
Canada is already at the forefront of ML and AI innovation. Through continued
investment in ML/AI for the EV manufacturing space, I believe we can become a
world leader in the ML/AI required for EV and battery production.
Q: The automotive industry, and the automobile itself, is centered more
and more on data. Does the role of data in EV manufacturing differ from
its role in non-EV manufacturing?
Cutulenco: Data is important whether you're building parts for internal-combustion-engine
(ICE) vehicles, off-highway vehicles or EVs. With EV part production
specifically, there is a need to use manufacturing data to accelerate
speed to market. Data can help EV component manufacturers reduce test
times, innovate faster during new-product introduction and ramp-up phases,
understand how new part designs will impact production and introduce new
products to market as quickly as possible.
A high level of precision is required when building EVs. For example, noise and
weight reduction are both big problems for EV manufacturing, which means that
manufacturers need new ways to innovate during production. More data will help
them deal with problems quicker, iterate on designs, launch new designs and drive
productivity. Manufacturers have had a hundred years to get to the point of stable,
predictable production of ICE vehicle parts. If we want to be at full EV production
in, let's say, 10 years, we need faster innovation - which means manufacturers
need data, and they need AI.
Q: Have you observed a difference in the uptake of AI within automotive
manufacturing due to the EV transition or hype around generative AI?
Cutulenco: Apart from vision systems - where AI seems to have been accepted
more fully in automotive manufacturing - we still see limited adoption of AI
and ML in manufacturing environments. Many still question the ability to operationalize
AI solutions in production, and a lot of effort is still required to drive
trust in these solutions with line engineers. Having said that, we are making
headway, and the EV transition is helping accelerate adoption. We're seeing
manufacturers move away from one-off AI projects, and we are leading the way
in terms of operationalized ML solutions. We're also expanding to more plants
within our growing customer base. Moreover, we are seeing more acceptance
of the idea of " predictive quality " in manufacturing, which is a concept we
have been touting within the industry for years. I guess you can say we like to
be ahead of trends.
http://www.acerta.ai
Automotive News Canada - August 2023

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