MechE Seminar: Data-driven manufacturing with additive manufacturing focus
Event details
| Date | 16.02.2022 |
| Hour | 13:30 › 14:30 |
| Speaker | Ms Ying Zhang, McGill University |
| Location | Online |
| Category | Conferences - Seminars |
| Event Language | English |
Abstract: Data-driven manufacturing is an approach to leverage data across the product lifecycle into manufacturing intelligence to guide decision-making. It enables manufacturers and designers to make better decisions to reduce costs and increase efficiency. This talk aims to present an application of data-driven analysis in additive manufacturing (AM). AM is a new trend of the manufacturing process which has been widely adopted in multiple industries for various purposes. One of the key challenges in employing AM for part fabrication is to determine the manufacturability of the given design. To fill this gap, an investigation of using the machine learning (ML) method to assess the manufacturability of designs for AM processes is carried out. A web-based tool as the final delivery can serve as a first-level evaluation of designs for novice AM users to reduce the waste of time and cost in AM fabrications. Specific challenges associated with ML-assisted applications in design and manufacturing and roadblocks towards data-driven manufacturing will be also discussed.
Bio: Ying Zhang is a Ph.D. candidate at McGill University in Canada supervised by Professor Yaoyao Fiona Zhao. Ying has submitted her initial thesis and is on the track to graduation. Her current research projects focus on data-driven approaches in additive manufacturing applications. Prior to her relocation to Canada in 2018, she had been a software and process engineer for almost two years in China. Moreover, Ying received her bachelor’s degree and master’s degree from the Georgia Institute of Technology in the United State with the guidance of Professor David W. Rosen.
Bio: Ying Zhang is a Ph.D. candidate at McGill University in Canada supervised by Professor Yaoyao Fiona Zhao. Ying has submitted her initial thesis and is on the track to graduation. Her current research projects focus on data-driven approaches in additive manufacturing applications. Prior to her relocation to Canada in 2018, she had been a software and process engineer for almost two years in China. Moreover, Ying received her bachelor’s degree and master’s degree from the Georgia Institute of Technology in the United State with the guidance of Professor David W. Rosen.
Practical information
- General public
- Free