Industrial Process & Profit
Optimization Software
Powered by ExplainableMachine Learning
New YorkUSA

Düsseldorf
Germany

65% of executives are not realizing
value from “AI” and Machine
Learning investments

MIT Sloan Management Review and BCG survey of 2,555
executives representing 29 industries and 97 countries

“AI” is presented as a
magic bullet
Most of it is hype

True “AI” does not exist yet and the term is acreation of marketers
Consultants pretend to “offer AI” to sell more
services
Software companies brand themselves as“AI” to benefit from the hypeThe biggest obstacle to the adoption ofMachine Learning in industry is trust.

Most Machine
Learning methods
struggle to drive
value for industry

Most ML software uses off-the-shelfalgorithms designed for the tech sector andnot applicable to industry
Traditional ML is black box, yet engineers
need to understand the root-cause of issues
Traditional ML optimization tools do not scale
to industrial systems, which leads to lower
ROI

Commodity dominated companies face
increasing competitive cost pressure.

The chemicals
industry is facing
many challenges instthe 21 century.

Specialty chemicals face constant pressure to
innovate and increase production volume, while
operating increasingly complex processes.
Demographic change increases pressure to run
plants more efficiently with fewer personnel.
Growing regulatory and financial pressure on
sustainability forces the chemical sector toincrease production volume, while reducing
energy consumption.

AI is not a magicbullet, but a very
powerful tool if
applied correctly bydomain experts

Our mission at Fero is to help industrial
companies turn their data into theircompetitive advantage, and:●generate quick, bottom-line returns,●

democratize machine learning across theorganization and succeed in digitization, and●build in-house data expertise via knowledgetransfer.

Fero Software Suite offers a range of optimization
applications tailored for industry
Process & Profit Optimization•••

Optimize plant metrics for efficiency, quality,
cost and sustainability
Discover main drivers for each metric anduse that to predict future values
Recommend optimal operating zones for theprocess

Asset Optimization•

Optimize asset metrics around efficiency•

Discover factors across the entire processthat impact individual asset degradation•Forecast and simulate optimal maintenanceschedule of assets to minimize maintenancecostsHow companies are staying ahead of thecurve using Fero’s explainable MLOptimize Batch Quality

Improve Asset Performance

Reduced raw material costs by 9%while reducing variability; developed 28
new products in a year at lower cost.

Identified root-causes of asset healthvariability and forecasted decline inperformance 30 days into the future.

Increase Yield

Average ROI
233%

Increased production yield 9-11% bymapping new relationships between
critical production parameters.

Reduce Emissions

Improved efficiency of the active filters
and analyzed over 4000 processparameters to reduce NOx emissions.

Fero’s ML understands and drives profits
UNDERSTAND: process & profit drivers

DRIVE: process & profit with precision

Prediction withconfidence band

Most machine learning techniques produce
black boxes; there is no way to understandhow critical inputs affect the outputs.
Fero software can identify how each input
affects the output and explain what leads tothe predictions.

Most machine learning algorithms only
predict a single value.
Fero software assigns a confidence bandto every prediction, allowing safer andmore precise decision making that drives
profits.

Used across the globe by industry leadersUse cases fromprocess industries

Optimize complex chemicalprocesses for yield

Fero Solution
9%-11% yield increase per process• Fero created digital twin of the plant to model
impacts on efficiency metrics such as yield• Amongst 1000+ process parameters,
identified factors that directly affect KPIs
• Mapped complex, non-linear relationships
between key inputs and targets outputs• Customer increased yield and loweredoperational costs* Will be presented jointly at Connected Plant 2020 conference(February 2020)

Root-cause analysis andscenario testing forcritical assets

Fero Solution
Reveal root-causes of heat exchanger
fouling while forecasting RUL• Fouling status of 100s of heat exchangers canbe tracked through Fero’s dashboard• Performance trends of individual assets are
predicted several weeks in advance• Maintenance engineers focus on the mostcritical assets with the shortest remaining life
• Process engineers analyze the root-causes ofthe failures to ensure increased reliability* Implementation presented by Covestro at OSI PI World, 2019.
The recording of the presentation is available online.

Soft sensor to minimize
cutter stock use at thecrude distillation unit

Top 3 O&G
Producer

Fero Solution$4M+ projected savings in the first year
• Loss of cutter stock to meet viscosity
specifications leads to reduced margins• Viscosity is a critical target, but it can be only
measured every 8 hours due to test limits• Fero predicts viscosity in real-time with highaccuracy and reveals the key factors
impacting the targets• Better informed operators adjust processduring production without waiting for tests

Reduce raw input
material costs while
maintaining quality

Fero Solution
Achieved 9% reduction in raw material
costs within the first year
• Cartersville used Fero to develop a new steel
chemistry that reduced raw material costs• “Accelerating product chemistry refinement
using ML” technical paper submitted to AIST
• Fero made sure key mechanical properties(tensile strength, yield strength, elongation)
are within target specs with high accuracy• Users are metallurgists, quality engineers,
process engineers and operators* Being scaled to multiple mills in NA.