Everyone knows artifcial intelligence has the potential to transform manufacturing: optimizing performance by taking all that data in the plant and supply chain and making it work better, faster, and automatically.
And experts believe these changes are coming soon. By 2030,
PwC predicts AI will add $6.6 trillion in productivity alone to the
What isn’t touted as loudly—though anyone who has tried
adding it to their operation will probably tell you—is that AI ain’t
a magic wand. It might not even be a tool sharp enough to cut
through your particular problems. An IDC survey found a quarter
of organizations reported up to a 50% failure rate.
That makes it tough on IIo T companies such as Flutura Decision Sciences & Analytics, a startup that launched its platform
Cerebra in 2013. In fact, they don’t even like to say AI.
“There’s still a little bit of misconception and ultimately what
[artifcial intelligence] can deliver and what vendors are actu-
ally selling,” Flutura general manager Greg Slater says. “Quite
honestly we don’t like to use the term ‘AI’ often because of all
the misconceptions in the industry. We like to call it ‘reliable
On the surface, the Cerebra SignalStudio platform, which
improves machine operations for oil & gas, specialty chemical
and heavy machinery industries, works just like any predic-
tive-preventative maintenance solution would. It employs sensor
and machine data and cloud-based AI to diagnose and prevent
failure and downtime, while maximizing asset performance reli-
ability and uptime and increasing yields and quality outcomes.
Where it differs is in its use of NanoApps—premade solutions
tailored to specifc industries and issues. These include the
Drilling Effciency App, Pressure Pumping App, Quality Bench
Marking App, Quality Simulation and Prognostics App, and
Yield Optimization App. It can detect welding defects using image analytics or fag dangerous work environments with video
analytics, such as a slippery foor or person not wearing PPE.
“We’re not an AI platform that is trying to boil the ocean; we
have a very surgical approach,” Slater explains.
The Houston-based company fancies itself the “FitBit for
Machines,” which is appropriate as the company founded in
2012 was conceptualized to help the medical industry before
it settled on the IIo T.
Flutura has about 30 clients currently, with adhesive manufacturer Henkel being the standout. Flutura helped predict a
quality issue that resulted in solving “a $300 million problem,”
The adhesives Henkel makes must meet very stringent
specifcations, as Bombardier uses them to bond its airplane
wings. At Henkel’s Shanghai Dragon plant, Cerebra started by
looking at historical data along the entire production line to
get a baseline for quality and what affects it. Then it started to
predict what materials must change based on environmental
factors and ultimately act to prevent bad batches, which could
lead to wasted time and product.
Each successful deployment adds to the effcacy of these
Slater says the Quality Simulation and Prognostic apps
got implemented at Henkel’s Dragon plant has scaled up to
more than 120 manufacturing lines across 15 countries for
just two customers.
The agile startup, which has been named to Gartner’s Magic
Quadrant for IIo T for the past two years, makes a bold promise to customers that despite industry statistics, this solution
won’t fail them.
“We guarantee that our customers, through our different
AI applications, will see value within 90 days or less,” Slater
says. “In the current environment, most of these initiatives are
designed as multi-year projects with benefts delivered almost
at the end of the cycle.”
In one case, Flutura set up a digital twin for a crude oil
extraction machine in 48 hours. An array of 500 sensor tags
continuously stream machine data to Cerebra to ensure the high
pressure (up to 9,000 psi) is not building up to a failure—and in
oil & gas, one hour of downtime could cost $200,000. Slater
believes that through a combination of digital twins, real-time
visibility and remote monitoring, there’s an opportunity to
unlock $8 billion worth of savings in the producing feld.
Cerebra also manages by exception, or fnding the data
or machine that doesn’t match the digital twin.
“We ignore the healthy assets and look at unhealthy
processes,” Slater says. “Then we drill down to root cause
analysis and take action against that and get that info out
to the feld.”
This helps prioritize human assets that may have to drive
to 50 oil wells in a day or travel across miles of factory foor
space. The technician or engineer goes to where the anom-
alies are frst, instead of a scheduled route, which can help
detect small problems before they turn into expensive ones.
And while the AI will get all the credit, the human element
is not forgotten. Along with frst-principles based models and
equations and real-time data, Cerebra adopts the tricks of
the trade coded within experienced workers’ brains, codifying the tribal knowledge for the entire organization to use.
“Real value is realized when all three sources of data are
leveraged together,” Slater says.
Failure is Not an Option for this
FLUTURA CEREBRA IIOT PLATFORM
By John Hitch
Many AI-enabled IIoT solutions promise big, transformative changes. This one has smaller goals, but guarantees