UMD Online Lectures
2023-03-13 | 活動
Lecture Schedule
| No. | Date (Hong Kong Time) | Lecture Topic |
| Year 2021 | ||
| 1 | 21-Jul-2021 | Development of canaries for Catastrophic failure prevention |
| 2 | 04-Aug-2021 | System Safety Verification and Validation For AI Systems |
| 3 | 11-Aug-2021 | Issues with Device Manufacturers Using Commercial-off-the-shelf Lithium-ion Batteries |
| 4 | 18-Aug-2021 | Degradation Analysis and Capacity Fade Prediction of Lithium-Ion Batteries |
| 5 | 01-Sep-2021 | Creation of life cycle profile for product reliability assessment |
| 6 | 15-Sep-2021 | Functional safety improvement through expanded diagnostic coverage |
| 7 | 29-Sep-2021 | Forecasting Maintenance: PHM Business Case Analysis |
| 8 | 13-Oct-2021 | Methods to ensure the reliability of sensors and the integrity of data produced by sensors |
| 9 | 27-Oct-2021 | Reliability and Failure Analysis for Electronics |
| 10 | 03-Nov-2021 | Application of prognostics in qualification |
| 11 | 10-Nov-2021 | Ensemble methods for individualized fault diagnosis |
| 12 | 17-Nov-2021 | How to achieve target safety integrity level (SIL) using PHM |
| 13 | 24-Nov-2021 | Conjugate-stress sensors for anomaly detection in structural health monitoring |
| 14 | 01-Dec-2021 | Reliability of Systems and Components After Storage: Management of Storage Process |
| 15 | 08-Dec-2021 | Role of Reliability Physics Modeling in Improving Diagnostic Coverage |
| 16 | 15-Dec-2021 | Improving Functional Safety and its Estimation using PHM for meeting SIL Targets |
| 17 | 22-Dec-2021 | Corrosion and Electro-Chemical Migration Prognostic Sensors |
| Year 2022 | ||
| 18 | 05-Jan-2022 | Component reliability assessment based on modeling and testing |
| 19 | 19-Jan-2022 | Simulation-Based Modeling for Prognostics |
| 20 | 16-Feb-2022 | Digital twins for reducing testing and qualification needed for safety assurance: Is the microelectronics industry ready ? |
| 21 | 23-Feb-2022 | The difficulty in duplicating field anomalies during laboratory post-mortems: A reliability physics perspective |
| 22 | 09-Mar-2022 | Reliability and Safety Analysis using Digital Twins |
| 23 | 23-Mar-2022 | Non-destructive methods of failure analysis |
| 24 | 06-Apr-2022 | Interpretability of Machine Learning Algorithms and Ensemble Learning Methods |
| 25 | 20-Apr-2022 | Product reliability validation for varying life cycle profile |
| 26 | 04-May-2022 | Prognostics-Based Qualification for Product Reliability Demonstration |
| 27 | 01-Jun-2022 | Potential of Augmenting Simulation-Based Component Reliability Assessment with Data-Driven Tools |
| 28 | 15-Jun-2022 | Fatigue Damage of Engineering Systems under Complex Vibration Environments |
| 29 | 28-Sep-2022 | Component Reliability Assessment Through Failure Mechanism Simulation |
| 30 | 19-Oct-2022 | Qualifications and Machine Learning |
| 31 | 16-Nov-2022 | Li dendrite formation in lithium-ion batteries - effects of battery materials |
| 32 | 30-Nov-2022 | Data-Driven Failure Analysis |
| 33 | 14-Dec-2022 | Thermal runaway in lithium-ion batteries - stages and causes |
| Year 2023 | ||
| 34 | 04-Jan-2023 | In-service assessment of lithium batteries for portable electronics |
| 35 | 18-Jan-2023 | The Sustainment for Transportation Systems |
| 36 | 01-Feb-2023 | Towards Interpretable Data-Driven Prognostics |
| 37 | 15-Feb-2023 | Power electronic component qualification using prognostic tools |
The HKSTP x CAiRS Public Seminar and Training Session on “Battery Performance, Ageing, Reliability, and Safety” addresses the crucial aspects to consider, especially with the increasing reliance on energy storage systems (ESS) like lithium-ion batteries. Understanding the Lithium dendrite growth dendrite growth process and revealing its interaction with other components can enable improvements in battery safety. Opportunities for novel information gathering and unique insights into the State of Health and State of Safety for batteries will also be explored. It will also include careful assessment of the thermal and mechanical profiles, certain cell anomalies can be discovered that might go unnoticed by conventional battery aging tests focusing solely on monitoring voltage, current, and capacity.
2024-09-04 | 活動The HKSTP x CAiRS Public Seminar and Training Session on “Battery Performance, Ageing, Reliability, and Safety” addresses the crucial aspects to consider, especially with the increasing reliance on energy storage systems (ESS) like lithium-ion batteries. Understanding the Lithium dendrite growth dendrite growth process and revealing its interaction with other components can enable improvements in battery safety. Opportunities for novel information gathering and unique insights into the State of Health and State of Safety for batteries will also be explored. It will also include careful assessment of the thermal and mechanical profiles, certain cell anomalies can be discovered that might go unnoticed by conventional battery aging tests focusing solely on monitoring voltage, current, and capacity.
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