Authors:
Ocan Şahin
;
Aslı Yasmal
;
Mustafa Samur
and
Gizem Kaya
Affiliation:
Turkish Petroleum Refinery, Körfez, Kocaeli, 41780, Turkey
Keyword(s):
Digital Twins, Process Optimization, Modelling, Simulation and Architecture, Real-Time Analysis, Decision Support Systems.
Abstract:
Refineries, operating with millions of dollars at stake, face significant economic consequences even with just 30 minutes of non-ideal operation. To address this challenge, this paper presents an industrial application of seamless integration of two different data sources into a complicated decision support tool that enables feedforward decisions. The integration is done in Node-RED, facilitating the data flow from two sources leveraging SOAP calls and COM interfaces in Python to automate the model manipulation, thus generating live estimates before operation takes place. A dashboard is developed, provides a user-friendly interface for visualizing the data and making informed decisions on how to increase efficiency and feed the existing model predictive control architecture. This use-case demonstrates the effectiveness of Node-RED in streamlining data integration, automation, and decision-making processes in industrial settings is demonstrated, contributing to improved operational ef
ficiency and profitability in the refinery industry.
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