智能数据驱动系统用于模具制造,使用强化学习和知识图个性化优化进行定制生产
Chengcai He1, Jiaxing Deng1, Jingchun Wu1
1Shenzhen Ruipengfei Mold Co., Ltd, Shenzhen City, 518000, China.
Scientific reports
|July 4, 2025
概括
本研究介绍了一种使用知识工程的优化模具数字化系统,以实现个性化的制造. 该系统提高了生产效率和质量控制,实现了超过94.7%的预测准确度.
科学领域:
- 制造业 工程 制造工程
- 人工智能的人工智能
- 知识工程知识工程知识工程
背景情况:
- 传统制造业依赖于标准化的工艺,限制了定制化.
- 个性化生产需要灵活和智能化的制造解决方案.
研究的目的:
- 为个性化制造开发一个优化的模具数字化系统.
- 整合知识图和智能算法用于智能质量控制.
- 为了提高模具制造中的定制能力.
主要方法:
- 利用知识工程将领域专业知识转换为可计算模型.
- 雇员强化学习和图形神经网络用于知识提取.
- 使用知识图和图形卷积网络开发了一个智能质量控制框架.
主要成果:
- 优化的系统实现了超过88.1%的合格率,具有强大的性能调整.
- 与其他模型相比,拟议的方法显示了超过94.7%的预测准确度.
- 该系统显著提高了模具制造的定制性,效率和质量.
结论:
- 优化的模具数字化系统为制造业的数字化转型提供了新的方向.
- 该方法使智能,灵活的生产能够满足个性化的产品需求.
- 该系统增强了制造商提供定制解决方案的能力,以高效和高质量提供定制解决方案.
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