[1]曹 笈,曹国富.焊管制造企业应用人工智能需优先解决的几个问题[J].焊管,2021,44(3):63-68.[doi:10.19291/j.cnki.1001-3938.2021.03.013]
 CAO Ji,CAO Guofu.Several Priority Problems in Application of Artificial Intelligence in Welded Pipe Manufacturing Enterprises[J].,2021,44(3):63-68.[doi:10.19291/j.cnki.1001-3938.2021.03.013]
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焊管制造企业应用人工智能需优先解决的几个问题()
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《焊管》[ISSN:1001-3938/CN:61-1160/TE]

卷:
第44卷
期数:
2021年第3期
页码:
63-68
栏目:
经验交流
出版日期:
2021-03-28

文章信息/Info

Title:
Several Priority Problems in Application of Artificial Intelligence in Welded Pipe Manufacturing Enterprises
文章编号:
10.19291/j.cnki.1001-3938.2021.03.013
作者:
曹 笈曹国富
嘉兴夏禹科技有限公司,浙江 嘉兴 314300
Author(s):
CAO Ji CAO Guofu
Jiaxing Xiayu Technology Co., Ltd., Jiaxing 314300, Zhejiang, China
关键词:
焊管制造人工智能智能制管生产数据
Keywords:
welded pipe manufacturing artificial intelligence intelligent manufacturing of pipe production data
分类号:
TG334.9
DOI:
10.19291/j.cnki.1001-3938.2021.03.013
文献标志码:
B
摘要:
人工智能正以前所未有的深度、广度和速度走进人类的生产、生活领域,分析了焊管行业应用人工智能、实现智能制管的可行性和必然性,指出为了实现智能制管,焊管生产企业要有坚定的信心,需要优先解决成本投入、生产数据收集、组建专家团队和机构、提高设备和管坯精度等问题,从数据、人才、组织、设备、管坯、管理等方面入手,为实现智能制管提前做好准备。
Abstract:
Artificial intelligence is entering the field of human production and life with unprecedented depth, breadth and speed. The feasibility and inevitability of applying artificial intelligence and realizing intelligent pipe making in welded pipe industry are analyzed. It is pointed out that in order to realize intelligent pipe making, the welding pipe production enterprises should have firm confidence, and should give priority to solve the problems such as cost input, production data collection, establishment of expert team and organization, improvement of equipment and tube blank precision, etc. From data, talent, organization, equipment, tube blank, management and other aspects, the preparations to realize intelligent tube making has been made.

参考文献/References:

[1] 曹国富,曹笈. 高频直缝焊管理论与实践[M]. 北京:冶金工业出版社,2016.

[2] KIM H,HA J,PARK J. Fault log recovery using an incomplete-data-trained FDA classifier for failure diagnosis of engineered systems [J]. International Journal of Prognostics and Health Management,2016(4):1-10.
[3] 武昌俊. 自动检测技术及应用[M]. 北京:机械工业出版社,2010.
[4] 史忠植. 人工智能[M]. 北京:机械工业出版社,2016.
[5] 曹国富. 直缝焊管用轧辊虚拟智造技术[J]. 焊管,2016(6):34-37.
[6] HARRINGTON P. 机器学习实战[M]. 李锐,李鹏,曲亚东,等译. 北京: 人民邮电出版社,2013.
[7] KIM H,HWANG T,PARK J,et al. Risk prediction of engineering assets: an ensemble of part lifespan calculation and usage classification methods[J]. International Journal of Prognostics and Health Management,2014,5(2):1-7.
[8] 曹国富. 管坯宽度数学模型[J]. 焊管,1998(3):15-19.
[9] 曹笈,曹国富. 焊管智造AI+高频直缝焊管制造的构想[J]. 焊管,2020(1):49-56.
[10] WEI X. A probabilistic machine learning approach to detect industrial plant faults[J]. International Journal of Prognostics and Health Managnment,2016,7(1):1-11.
[11] 钱显毅. 传感器原理与检测技术[M]. 北京:机械工业出版社,2011.

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备注/Memo

备注/Memo:
收稿日期:2021-01-18
作者简介:曹 笈(1982—),博士,主要研究方向为微电子技术。
更新日期/Last Update: 2021-05-08