研究概要

现有以深度学习为基础的人工智能技术本质上是非可信的,这限制了人工智能方法在以可靠性为基本要求的制造业中的应用,成为智能制造发展的根本性瓶颈所在。本项目团队围绕人工智能非可信性与智能制造可靠性之间的根本性矛盾,研究解决如下关键问题:智能制造环境下非可信智能的表征和边界判定;面向可靠智造的智能可信边界拓展方法框架和智能可信边界受限下的可靠智造方法框架。通过以上研究,系统性提出非可信智能下可靠智造的理论和方法框架,并依托联宝(合肥)电子科技有限公司笔记本生产全流程打造可靠智造示范样板,推动安徽省在智能制造领域的突破性发展,助力“中国制造2025”国家重大战略。

主要研究内容

  • 智能制造环境下非可信智能的的表征和边界判定
  • 面向可靠智造的智能可信边界拓展方法框架
  • 智能可信边界受限下的可靠智造方法框架

基本研究框架

相关阅读

研究成果

Conference Articles

  1. A Reliable Ensemble Model Based on Hierarchical Component Features for Repair Label Prediction of Soldering Defects Longxin Chen, Yunbo Zhao, Binkun Liu, Shaojie Dong, Huijuan Zhu, and Peng Bai In 2024 14th Asian Control Conf. ASCC 2024 [Abs] [pdf]
  2. A Real-time Detection Method for SMT Chip Component Defects Based on Adaptive Collaborative Feature Yunbo Zhao, Wangyou Gui, Yu Kang, Kehao Shi, Lijun Zhao, and Zhenyi Xu In 2024 International Conference on Guidance, Navigation and Control (ICGNC 2024) 2024 [Abs] [pdf]
  3. Prediction of Yield in Functional Testing of Motherboards in Laptop Manufacturing Yunbo Zhao, Shaojie Dong, Yu Kang, Kangcheng Wang, Longxin Chen, and Peng Bai In 2024 14th Asian Control Conf. ASCC 2024 [Abs] [pdf]
  4. Functional Test-Cost Reduction Based on Fault Tree Analysis and Binary Optimization Xiaojie Zuo, Kangcheng Wang, Yun-Bo Zhao , Yu Kang, and Peng Bai In 2024 43rd Chin. Control Conf. CCC 2024 [doi] [pdf]
  5. Spectrally Normalized Adaptive Neural Identifier for Dynamic Modeling and Trajectory Tracking Control of Unmanned Aerial Vehicle Shaofeng Chen, Yu Kang, Yunbo Zhao, and Yang Cao In Adv. Guid. Navig. Control 2023 [Abs] [doi] [pdf]
  6. Board-Level Functional Test Selection Based on Fault Tree Analysis Yaoyao Li, Kangcheng Wang, Yu Kang, Yunbo Zhao, and Peng Bai In 2023 6th Int. Symp. Auton. Syst. ISAS 2023 [Abs] [doi] [pdf]
  7. A Feature Engineering-based Method for PCB Solder Paste Position Offset Prediction Binkun Liu, Yunbo Zhao, Yu Kang, Yang Cao, Peng Bai, and Zhenyi Xu In 2023 6th Int. Symp. Auton. Syst. ISAS 2023 [Abs] [doi] [pdf]
  8. Defect Detection of Laptop Appearance Based on Improved Multi-Scale Normalizing Flows Jie Zhang, Zerui Li, and Yunbo Zhao In 2023 38th Youth Acad. Annu. Conf. Chin. Assoc. Autom. YAC 2023 [Abs] [doi] [pdf]
  9. Shared Autonomy Based on Human-in-the-loop Reinforcement Learning with Policy Constraints Ming Li, Yu Kang, Yun-Bo Zhao , Jin Zhu, and Shiyi You In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]
  10. A Robustness Benchmark for Prognostics and Health Management Binkun Liu, Yun-Bo Zhao , Yang Cao, Yu Kang, and Zhenyi Xu In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]
  11. Equipment Health Assessment Based on AHP-CRITIC Dynamic Weight Yunsheng Zhao, Pengfei Li, Tao Wang, Yu Kang, and Yun-Bo Zhao In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]
  12. Anomaly Detection for Surface of Laptop Computer Based on Patchcore Gan Algorithm Huijuan Zhu, Yu Kang, Yun-Bo Zhao , Xiaohui Yan, and Junqiang Zhang In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]

Journal Articles

  1. Deep Reinforcement Learning for Maintenance Optimization of Multi-Component Production Systems Considering Quality and Production Plan Ming Chen, Yu Kang, Kun Li, Pengfei Li, and Yun-Bo Zhao Quality Engineering 2024 [doi] [pdf]
  2. Modelling and Optimizing Motherboard Functional Testing in Laptop Manufacturing Yu Kang, Peng Bai, Kangcheng Wang, and Yun-Bo Zhao J. Syst. Sci. Complex. 2024 [Abs] [doi] [pdf]
  3. Multivariate Time Series Modeling and Forecasting with Parallelized Convolution and Decomposed Sparse-Transformer Shusen Ma, Yun-Bo Zhao , Yu Kang, and Peng Bai IEEE Trans. Artif. Intell. 2024 [Abs] [doi] [pdf]
  4. A Health Indicator Enabling Both First Predicting Time Detection and Remaining Useful Life Prediction: Application to Rotating Machinery Yun-Sheng Zhao, Pengfei Li, Yu Kang, and Yun-Bo Zhao Measurement 2024 [Abs] [doi] [pdf]
  5. Cross-Sensor Generative Self-Supervised Learning Network for Fault Detection Under Few Sample Huijuan Zhu, Yun-Bo Zhao , Xiaohui Yan, Yu Kang, and Binkun Liu J. Syst. Sci. Complex. 2024 [Abs] [pdf]
  6. 非全时有效人类决策下的人机共享自主方法 游诗艺, 康宇, 赵云波, and 张倩倩 中国科学:信息科学 2022 [Abs] [doi] [pdf]

Book Chapters

  1. SMT Component Defection Reassessment Based on Siamese Network Chengkai Yu, Yun-Bo Zhao , and Zhenyi Xu In Methods and Applications for Modeling and Simulation of Complex Systems 2022 [Abs] [doi] [pdf]

patent

  1. 基于跨模态生成式学习的液压减震器设备异常检测方法 赵云波, 朱慧娟, 闫晓辉, and 康宇 2023 [pdf]
  2. 锡膏印刷机参数调整数据处理软件V1.0 许镇义, 刘斌琨, 康宇, 曹洋, and 赵云波 2022 [pdf]
  3. 锡膏印刷机离线故障预测软件V1.0 赵云波, 刘斌琨, 曹洋, 康宇, and 许镇义 2022 [pdf]
  4. 锡膏印刷机在线故障预测软件V1.0 赵云波, 陈龙鑫, 朱慧娟, 康宇, and 许镇义 2022 [Abs] [pdf]
  5. 基于特征工程的PCB板焊盘偏移预测方法及存储介质 曹洋, 刘斌琨, 赵云波, 康宇, and 许镇义 [Abs]
  6. 一种基于多传感器特征融合的轴承故障诊断方法 康宇, 刘斌琨, 赵云波, 许镇义, and 曹洋
  7. 一种基于时间重构图卷积的PCB锡膏印刷质量预测方法 康宇, 刘斌琨, 赵云波, 曹洋, 许镇义, and 柏鹏 [Abs]
  8. 贴片机的健康度评估方法及系统 李鹏飞, 赵昀昇, 康宇, 赵云波, and 王涛 [Abs]
  9. 印刷电路板的微小缺陷检测方法及存储介质 许镇义, 余程凯, 曹洋, 康宇, and 赵云波 [Abs]
  10. 用于PCB微小缺陷检测的单帧目标检测方法及存储介质 许镇义, 桂旺友, 曹洋, 康宇, and 赵云波 [Abs]
  11. 一种基于特征迁移的轴承剩余使用寿命预测方法 许镇义, 刘斌琨, 康宇, 赵云波, and 曹洋 [Abs]
  12. 一种基于多任务学习机制的PCB缺陷检测方法、系统 许镇义, 房明亮, 曹洋, 康宇, and 赵云波 [Abs]
  13. 一种细粒度自适应主板功能测项选择方法及系统 赵云波, 李瑶瑶, 王康成, 康宇, and 柏鹏 [Abs]
  14. 一种基于金字塔增强网络的低光照下目标检测方法 赵云波, 尹相臣, 李泽瑞, 于桢达, and 康宇 [Abs]
  15. 减震器故障检测方法、装置、设备及存储介质 赵云波, 刘斌琨, 康宇, 曹洋, and 许镇义 [Abs]
  16. 故障诊断模型的训练方法、装置、电子设备及存储介质 赵云波, 陈龙鑫, 刘斌琨, 朱慧娟, 许镇义, and 柏鹏 [Abs]
  17. 产线设备故障预测方法、装置、电子设备及存储介质 赵云波, 董少杰, 刘斌琨, 朱慧娟, 许镇义, and 柏鹏 [Abs]
  18. 一种基于故障树和相关性分析的动态测项良率计算方法 赵云波, 马树森, 王康成, 康宇, and 柏鹏 [Abs]
  19. 融合决策树和故障树分析的主板功能测试策略设计方法 赵云波, 李瑶瑶, 王康成, 康宇, and 柏鹏 [Abs]
  20. 一种基于可靠性分析的主板功能测试策略方法及系统 赵云波, 李瑶瑶, 王康成, 康宇, and 柏鹏 [Abs]
  21. 基于多尺度标准化流的无监督笔记本外观缺陷检测方法 赵云波, 张杰, 李泽瑞, 康宇, and 吕文君 [Abs]
  22. 笔记本生产线受损监控信息快速修复方法及存储介质 朱进, 黄蕾, and 赵云波 [Abs]

项目人员

赵云波 何创创 余程凯 刘斌琨 刘朝虎 张天浩 张年坤 张杰 朱慧娟 李佳玉 李瑶瑶 桂旺友 欧阳晨 王晓蓥 罗里恒 范冰 董少杰 谢飞 赵昀昇 陈明 陈龙鑫 青凡迪 马树森 齐振宇

项目合作

  • 康宇 教授, 中国科学技术大学自动化系
  • 张倩倩 讲师, 安徽大学人工智能学院
  • 朱进 副教授, 中国科学技术大学自动化系
  • 李鹏飞 特任副研究员, 中国科学技术大学自动化系
  • 王康成 博士后, 合肥综合性国家科学中心人工智能研究院