Machine Learning an Intelligent Approach in Process Industries: A Perspective and Overview

被引:15
作者
Khan, Nadia [1 ]
Taqvi, Syed Ali Ammar [2 ]
机构
[1] NED Univ Engn & Technol, Polymer & Petrochem Engn Dept, Karachi, Pakistan
[2] NED Univ Engn & Technol, Chem Engn Dept, Karachi, Pakistan
关键词
Artificial intelligence; Fault detection; Machine learning; Predictive analysis; Process industries; WATER TREATMENT-PLANT; NEURAL-NETWORK ANN; WASTE-WATER; ARTIFICIAL-INTELLIGENCE; DISTILLATION COLUMN; FAULT-DETECTION; MAIZE YIELD; PREDICTION; OIL; MODEL;
D O I
10.1002/cben.202200030
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The field of machine learning has proven to be a powerful approach in smart manufacturing and processing in the chemical and process industries. This review provides a systematic overview of current state of artificial intelligence and machine learning and their applications in textile, nuclear power plant, fertilizer, water treatment, and oil and gas industries. Moreover, this study reveals the current dominant machine learning methods, pre and post processing of models, increased utilization of machine learning in terms of fault detection, prediction, optimization, quality control, and maintenance in these sectors. In addition, this review gives the insight into the actual benefits and impact of each method, and complications in their extensive deployment. Finally in the current impressive state, challenges, future development in terms of algorithm and infrastructure aspects are highlighted.
引用
收藏
页码:195 / 221
页数:27
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