Review of synergy between machine learning and first principles models for asset integrity management

IF 2.5 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Frontiers in chemical engineering Pub Date : 2023-07-12 DOI:10.3389/fceng.2023.1138283
Tianxing Cai, Jian Fang, Sharath Daida, H. Lou
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引用次数: 0

Abstract

The chemical process industry (CPI) accumulated a rich data asset through industrial 4.0. There is a strong drive to develop and utilize effective approaches for process performance prediction and improvement, process control, sensor development, asset management, etc. The synergy between machine learning and first principles models can bring new insights and add tremendous value to the CPI. This paper reviews various applications of the synergies towards asset integrity management. An overview of some related commercial software packages are also provided.
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资产完整性管理中机器学习与第一性原理模型的协同作用综述
化工过程工业(CPI)通过工业4.0积累了丰富的数据资产。开发和利用过程性能预测和改进、过程控制、传感器开发、资产管理等有效方法的动力很大。机器学习和第一性原理模型之间的协同作用可以带来新的见解,并为CPI增加巨大价值。本文综述了协同效应在资产完整性管理中的各种应用。还提供了一些相关商业软件包的概述。
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来源期刊
CiteScore
3.50
自引率
0.00%
发文量
0
审稿时长
13 weeks
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