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AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

AI in the Chemical Industry: The Power of the Virtual Sensor

Sergio Hernández
MES/MOM Director
-
AG Solution Group
The impact of AI in the chemical industry due to corrosive environments is evident.

In a recent opinion column published in the digital version of Automática e Instrumentación, a renowned industry-focused media outlet in Spain, Sergio Hernández, AG Solution Group's MES Director, delves into the transformative role of Artificial Intelligence (AI) in the chemical industry. We are pleased to present a summarized version of his insights here, emphasizing the groundbreaking potential of the virtual sensor in maintaining plant assets, particularly in corrosive environments.

The chemical industry thrives on the meticulous upkeep of plant assets. This becomes particularly intricate when maintaining, configuring, and calibrating sensors in corrosive environments, ensuring accurate process readings. The downtime and efficiency loss resulting from these activities can jeopardize the final product's quality, bringing about unnecessary costs. So, how does AI come into play?

AI, specifically Machine Learning (ML), can be trained on vast amounts of data to create a "virtual sensor" that predicts real-time PH values without relying on physical sensors. The implications?

  • Steadier Production: Proactive adjustments ensure product quality remains intact by anticipating PH value shifts.
  • Reduced Maintenance: Accurate predictions allow for streamlined maintenance schedules and cost savings.

However, these ML models thrive on ample data from control systems in compliance with ISA S95 standards. Hence, a robust SCADA, DCS, or Historian system is essential. Integrating this with data treatment stations is equally crucial, ensuring the predicted values inform the supervisory control and data acquisition.

To harness AI's full potential in this realm, one must:

  • Have abundant multivariable data for both supervised and unsupervised learning.
  • Model accurately, removing outliers and leveraging suitable algorithms.
  • Ensure seamless integration between ML software tools and control systems.
  • Possess an in-depth understanding of the process, marrying expertise from the chemical industry and data professionals.

AI's impact on the chemical industry, especially in corrosive settings, is transformative. While this article highlights the PH sensor's virtualization, AI's applications in equipment maintenance, whether predictive maintenance in centrifugal pumps or motors are vast and ever-expanding.


[Read the complete article in Spanish.]

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