How will the Process
from adopting AI?
Artificial intelligence proposes a radically different approach to the traditional scientific method. It wants to automate the learning processes of that experienced operator.
Because although humans are smarter, computers are faster. And luckily humans are smart enough to make computers mimic the human learning process.
These are AI algorithms.
TOWARDS FULLY AUTOMATED
plants and enterprises
Having the need to know the underlying mechanics in order to develop better mathematical models is slowing the whole process down significantly. Much more valuable is that experience-based expert operator’s knowledge… Isn’t it?
Talk to your Faktion AI Consultant to learn how we can accelerate this whole process and what the benefits are.
An experience-based expert
operator's knowledge is not enough
An ai toolbox
to classical mathematical models
ArtificiaI Intelligence looks at the experiments and
measurements and derives the model from that data.
That’s why many AI algorithms are called ‘learning’
algorithms. They learn the solution without any prior paradigm, just from the data.
Technically, it is important to understand that this happens very much like human experienced-based learning: by repeated trial and error. AI algorithms provide the procedure to try something out, learn from it, adapt the model intelligently for the next time and then try it again.
Very general and broad
Fast training, development
Very specific and precise
Based on correlations
should always be the goal
The potential for business value creation is especially large in the process industry, given the complexity and high value of the industry.
Today, processing plants have already made substantial
investments in process monitoring with mostly traditional and some AI-powered sensor tech. These sensors ‘measure’ the process and the resulting state of the process.
However, operators must still rely on their experience, intuition, and judgment for process analysis and control. They are expected to monitor a multitude of information and adjust the process settings as required.
At the same time, they must troubleshoot and run tests and trials. Thus, many operators take shortcuts and prioritize urgent activities that don’t necessarily add value.
What are the drivers behind an
AI implementation in this industry?
of the process industry
Many continuous processes require
Marginal improvements yield
large bottom-line results
of process managers
Scarce & expensive
labor force with expertise
Sensors to detect anomalies
humans can’t detect
there is so much more
and we are here to help
We are aware that the value for companies is not in the theory, but in seeing potential applications.
For the implementation, everything is there, expert AI service companies exist, and the basic theory is mature enough to be implemented in a controlled and targeted fashion.
At the same time, the AI framework is disruptive enough for the results to be not less than breakthroughs.