Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization

As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization...

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Autores principales:	Faraz Qasim, Doug Hyung Lee, Jongkuk Won, Jin-Kuk Ha, Sang Jin Park
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	failure mode FMEA FTA RCA cause and effect decision support system Technology T
Acceso en línea:	https://doaj.org/article/e4bc01c97d9c421bb749eb0444cfa72e
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spelling	oai:doaj.org-article:e4bc01c97d9c421bb749eb0444cfa72e2021-11-11T15:57:25ZDevelopment of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization10.3390/en142171831996-1073https://doaj.org/article/e4bc01c97d9c421bb749eb0444cfa72e2021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/7183https://doaj.org/toc/1996-1073As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization and safety. Big data and knowledge-based platforms are receiving much attention to provide a comprehensive decision support system. In this study, the Advanced Advisory system for Anomalies (AAA) is developed to predict and detect the abnormal operation in fired heaters for real-time process safety and optimization in a petrochemical plant. This system predicts and raises an alarm for future problems and detects and diagnoses abnormal conditions using root cause analysis (RCA), using the combination of FMEA (failure mode and effects analysis) and FTA (fault tree analysis) techniques. The developed AAA system has been integrated with databases in a petrochemical plant, and the results have been validated well by testing the application over an extensive period. This AAA online system provides a flexible architecture, and it can also be integrated into other systems or databases available at different levels in a plant. This automated AAA platform continuously monitors the operation, checks the dynamic conditions configured in it, and raises an alarm if the statistics exceed their control thresholds. Moreover, the effect of heaters’ abnormal conditions on efficiency and other KPIs (key performance indicators) is studied to explore the scope of improvement in heaters’ operation.Faraz QasimDoug Hyung LeeJongkuk WonJin-Kuk HaSang Jin ParkMDPI AGarticlefailure modeFMEAFTARCAcause and effectdecision support systemTechnologyTENEnergies, Vol 14, Iss 7183, p 7183 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	failure mode FMEA FTA RCA cause and effect decision support system Technology T
spellingShingle	failure mode FMEA FTA RCA cause and effect decision support system Technology T Faraz Qasim Doug Hyung Lee Jongkuk Won Jin-Kuk Ha Sang Jin Park Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization
description	As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization and safety. Big data and knowledge-based platforms are receiving much attention to provide a comprehensive decision support system. In this study, the Advanced Advisory system for Anomalies (AAA) is developed to predict and detect the abnormal operation in fired heaters for real-time process safety and optimization in a petrochemical plant. This system predicts and raises an alarm for future problems and detects and diagnoses abnormal conditions using root cause analysis (RCA), using the combination of FMEA (failure mode and effects analysis) and FTA (fault tree analysis) techniques. The developed AAA system has been integrated with databases in a petrochemical plant, and the results have been validated well by testing the application over an extensive period. This AAA online system provides a flexible architecture, and it can also be integrated into other systems or databases available at different levels in a plant. This automated AAA platform continuously monitors the operation, checks the dynamic conditions configured in it, and raises an alarm if the statistics exceed their control thresholds. Moreover, the effect of heaters’ abnormal conditions on efficiency and other KPIs (key performance indicators) is studied to explore the scope of improvement in heaters’ operation.
format	article
author	Faraz Qasim Doug Hyung Lee Jongkuk Won Jin-Kuk Ha Sang Jin Park
author_facet	Faraz Qasim Doug Hyung Lee Jongkuk Won Jin-Kuk Ha Sang Jin Park
author_sort	Faraz Qasim
title	Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization
title_short	Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization
title_full	Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization
title_fullStr	Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization
title_full_unstemmed	Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization
title_sort	development of advanced advisory system for anomalies (aaa) to predict and detect the abnormal operation in fired heaters for real time process safety and optimization
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e4bc01c97d9c421bb749eb0444cfa72e
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Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization

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