World Grain - September 2024 - 44

perature, according to Omas.
" This system helps bridge the gap
between traditional
milling
practices
and the digital future, ensuring
that customers benefit from the latest
advancements in the industry, "
Barbalarga said.
Ideally,
AI would be specialized
to perform a specific operation,
Demirtaşoğlu of DESMÜD said. A subFabrizio
Baccinelli, sales director at Ocrim.
In addition to the milling process, preventive maintenance
and energy optimization within the mill
are other areas to consider for AI, he said.
Rolling with AI
The machines are one thing, but the applications
of those machines in the use of
different raw products is another level.
The reactions of raw materials at each step
toward the desired end products require millers
to make precise adjustments in the process.
With so many inputs at so many places, the tiniest
Demirtaşoglu
change can have profound consequences on the flour quality
characteristics.
Omas' Barbalarga said AI can offer significant
advantages.
* Process optimization: enhancing energy
efficiency, reducing waste, and optimizing
the use of raw materials through continuous
analysis of production data.
* Predictive maintenance: predicting
and preventing machine breakdowns, reGwirtz
ducing
downtime and maintenance costs.
* Quality control: detecting real-time
anomalies in product quality, ensuring consistent
and standard-compliant production.
" There is a growing interest in better understanding
AI and its applications, and many customers are seeking
information and training to fully grasp how to leverage
this technology, " he said. " In my opinion,
it's important to highlight that the role of the
miller is becoming increasingly valuable yet
scarce, with an emerging need to digitize
processes. This shift is particularly important
in attracting new generations to
the field, as digital tools and automation
can make the profession more accessible
and appealing. "
Baccinelli
One initiative of Omas has been the Omas
Milling Pilot, a system designed to explore and
implement cutting-edge technologies in the milling process.
This system represents a step toward AI in mill
control, automating the regulation of rollers and tem44
set
of AI, machine learning in which computer programs
spontaneously learn and apply new data without any human
guidance. Such deep learning techniques enable the
automatic learning of large amounts of ungrouped data
such as text, images, graphics or video.
" As technology advances, previous criteria for defining
artificial intelligence are becoming obsolete, " he said.
" For example, the work done by machines that compute
basic functions or recognize text through optical character
recognition is no longer considered a function of
artificial intelligence, but a normal computer function. "
The stability of the wheat milling process over thousands
of years, despite its complexity, tends to provide a
comfort level that is appealing to millers and their customers,
even as technology has added to its efficiency
and ability to refine outcomes and nutritional values. AI
might allow the process to more quickly adapt to unforeseen
challenges.
Automation has helped milling operations become
more effective and streamlined, said Gonzalez of Bühler,
which has its global headquarters in Uzwil, Switzerland.
However, automation doesn't provide analytics, and the
limited solutions in the market are ineffective in providing
recommendations, benchmarking, comparisons, etc.
This type of intelligence is critical to improve operations.
Many points during production gather data but are not effective
at analyzing this data, or there is no analytics at all.
" With the challenges that the market is facing and the
small margins from the industry, it is critical to have
effective analytic solutions that help our customers improve
and remain competitive in the market, " Gonzalez
said. " I believe AI will bring the edge needed to the
operations and aid in improving production. "
Gonzalez said most of Bühler's work with AI is for
specific cases from customers trying to identify an issue
or improve a process, and the clearest example is
with its Sortex machines.
" The image processing models have been trained
to make a more effective selection of the produce that
needs to be discarded, like grain affected by pests, nonwheat
grains, rocks, etc. Bühler's latest Sortex machines
have leapt into better product selection thanks to AI and
machine learning, " he said.
Gwirtz, of JAG services, emphasized the human factor
September 2024 / World Grain / World-Grain.com
© Parilov-stock.adobe.com, Desmüd, Jeff Gwirtz
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World Grain - September 2024

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