工艺安全
过程(计算)
制造工程
风险分析(工程)
背景(考古学)
危险废物
质量(理念)
工程类
制造业
计算机科学
业务
过程管理
知识管理
在制品
运营管理
操作系统
生物
古生物学
营销
认识论
哲学
废物管理
作者
Shuai Mao,Wang Bing,Yang Tang,Feng Qian
出处
期刊:Engineering
[Elsevier BV]
日期:2019-11-03
卷期号:5 (6): 995-1002
被引量:178
标识
DOI:10.1016/j.eng.2019.08.013
摘要
Abstract Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process-safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging information technologies such as artificial intelligence (AI) are quite promising as a means of overcoming these difficulties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety; ② knowledge-based reasoning for process safety; ③ accurate fusion of heterogeneous data from various sources; and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.
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