人工智能的新应用:利用隐性知识启动液化天然气工厂

Kian Seng Lee, Xin Wei Yeap, Elaine Synn Yie Khoo, Yong Xian Lee, Shiuan Yong, Yi Han Hiew, Hafiz Maamor, Saifuddin Zulkaple
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引用次数: 0

摘要

为了从熟练的操作人员那里获取宝贵的隐性知识,并利用从20多年的工厂运行数据中产生的见解,开发了一种人工智能驱动的实时咨询,为操作人员在启动期间提供实时参数控制咨询,以响应实际的过程和设备条件。该解决方案已被部署到马来西亚液化天然气公司的10家初创企业中,成功地减少了44%的持续时间,减少了17%的碳排放。较短的启动时间转化为从生产机会中创造的巨大价值,在短短15个月内产生了令人印象深刻的35的投资回报。此外,与过去20年的所有历史事件相比,其中6家初创企业也成为执行力最高的企业,这表明它有能力支持持续和优化的初创企业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Application of AI: Harnessing Tacit Knowledge for LNG Plant Start-Up
To capture the invaluable tacit knowledge from skilled operators and leverage on insights generated from over two decades of plant operation data, an AI-driven live advisory was developed to provide operators with real-time parameters control advisory during start-up, in response to actual process and equipment conditions. The solution had been deployed to ten start-ups in Malaysia LNG, successfully achieving 44% reduction in duration and 17% reduction in carbon emission from reduced gas usage. The shorter start-up duration translated into significant value creation from production opportunity, yielding an impressive return on investment of 35, in just 15 months. Furthermore, six of the start-ups also emerged as the top executions when benchmarked against all historical occurrences in the past two decades, demonstrating its ability to enable consistent and optimised start-ups.
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