World Grain - September 2024 - 70

FEATURE: Q&A WITH BÜHLER'S ALEXIS NÖEL
Data collected from digital solutions helps us drive continuous
improvement and innovation in flour milling by uncovering trends and
patterns that guide strategic decisions and process optimizations.
Alexis Nöel, Bühler's digital program manager
WG: What are some of the challenges in transitioning
and familiarizing customers with new digital solutions?
Nöel: Transitioning and familiarizing customers with
new digital solutions in the flour milling industry faces
several challenges. Resistance to change is significant.
The high initial costs and uncertainty about the return on
investment (ROI) complicate the transition. Technical
complexity, such as integrating new digital tools with existing
systems and effectively managing large volumes of
data, poses some obstacles. Additionally, employees often
lack the necessary technical skills to operate and maintain
these new systems, making comprehensive training
programs essential but time-consuming and costly.
Overcoming these challenges requires strategic planning,
clear communication about the benefits, and investment
in training and support to ensure a smooth transition to
digital solutions.
WG: Digital solutions collect a lot of data. How is
Bühler using this data to improve its technology and also
the milling process for customers?
Nöel: Data collected from digital solutions helps us
drive continuous improvement and innovation in flour
milling by uncovering trends and patterns that guide
strategic decisions and process optimizations. Advanced
analytics, including machine learning and AI, predict outcomes
and tailor solutions to specific operational needs.
Additionally, data on customer interactions and feedback
allows for the identification of needs and preferences, enabling
the development of customized solutions and services.
This customer-centric approach enhances our machines
development, service enhancements, and overall
customer satisfaction, leading to more personalized and
efficient milling operations.
WG: What methods has Bühler used to address this?
Nöel: The extensive and diverse data collected is crucial
for the success of advanced AI features. Bühler is
uniquely positioned to excel in this area due to its internally
developed platforms and software. Bühler machines
generate in-depth process data, which is enhanced by
the Mercury Manufacturing Execution System (MES).
Maintenance data from the Computerized Maintenance
Management System (CMMS) ProPlant also contributes
valuable insights.Additionally, the broad customer base
using these digital platforms accelerates data accumulation.
Early in this journey, Bühler established data scien70
tist
teams to develop proprietary models. These teams collaborate
with experienced milling technologists to address
the industry's most pressing challenges.
WG: What are the potential benefits and drawbacks to
the use of AI?
Nöel: The use of AI in various industries offers significant
benefits, such as enhanced efficiency and cost
savings. AI can optimize production processes, reducing
waste and improving yield, while predictive maintenance
minimizes downtime and maintenance costs.
Additionally, AI helps optimize resource use, such as
energy and raw materials, leading to significant cost savings
and labor efficiency by automating repetitive tasks.
However, there are notable drawbacks, including technical
challenges and dependence issues. AI systems require
high-quality data to function effectively, and poor data
quality can lead to erroneous conclusions. Integrating
AI with existing systems can be complex. Furthermore,
over-reliance on AI systems can be problematic if they fail
or produce incorrect results, and AI should complement
human decision-making to ensure balanced and efficient
outcomes. Balancing these benefits and drawbacks is crucial
for successful AI implementation.
WG: What are some of the areas where digital solutions/AI
will be able to assist in the future?
Nöel: In the future, digital solutions and AI will increasingly
enhance flour milling through advanced process
and machine adjustments, quality control and production
planning. AI algorithms will enable real-time adjustments
to milling processes and machinery, optimizing operational
parameters for improved efficiency and product quality.
By analyzing continuous data streams, AI will predict
equipment wear and automatically adjust settings to maintain
peak performance. In quality control, AI will provide
precise monitoring and analysis of flour characteristics,
ensuring consistent quality and rapid detection of deviations.
For production planning, AI will facilitate more accurate
forecasting and scheduling by analyzing historical
data, market trends, and demand patterns. This will enable
mills to optimize inventory levels, streamline operations,
and respond more swiftly to market changes, ultimately
enhancing overall productivity and competitiveness.
We want to hear from you - Send comments and inquiries
to worldgrain@sosland.com. For reprints of WG articles,
email reprints@sosland.com.
September 2024 / World Grain / World-Grain.com
http://www.World-Grain.com
World Grain - September 2024

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