嵌入式实时分析连续造用于机器支持的质量优化
Kersten Marx1, Yalçın Kaymak1, Zeinab Kargar2
1Process Optimisation Iron and Steel Making, VDEh-Betriebsforschungsinstitut GmbH, Düsseldorf, North Rhine-Westphalia, 40489, Germany.
这项研究开发了一个实时支持系统,用于预测连续造中顶部结事件,提高工厂的安全性. 该系统使用大数据和数字双胞胎来改善钢铁生产中的控制和缺陷预防.
科学领域:
- 材料科学 材料科学 材料科学
- 工艺工程的过程工程.
- 数据科学数据科学数据科学
背景情况:
- 由于许多因素,手动控制连续造 (CC) 具有挑战性.
- 手动的顶部结控制影响质量和故障风险.
- 未被检测到的顶部结事件构成了重要的工厂安全风险.
研究的目的:
- 为了数字化和优化连续造机.
- 开发一个实时支持系统,用于预测顶部结事件.
- 在连续造过程中改善控制和提高工厂安全.
主要方法:
- 利用线下材料跟踪,数据流同步和大数据分析.
- 开发了模具的离线3D数字双胞胎,考虑了热传递和固化.
- 通过CFD模拟评估的集成连续子输入变量,进入在线支持系统.
主要成果:
- 通过将统计结果与表面缺陷检测相关联,确定了促进缺陷的场景.
- 创建了一个3D数字双胞胎来研究影响顶部结的因素.
- 开发并培训了一个与工厂数据库连接的在线支持系统.
结论:
- 实时支持系统可以在整个造过程中预测顶部结事件.
- 显著提高了工厂的安全性,并允许有针对性的检查.
- 有助于优化钢铁生产,提高可靠性和缺陷预防.
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