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SUMMARY:MechE Seminar: Data-driven manufacturing with additive manufacturi
 ng focus
DTSTART:20220216T133000
DTEND:20220216T143000
DTSTAMP:20260407T120119Z
UID:279d9bd10eb0c007714a7ff38bf7567b90daef5e1f4633d2e6570eda
CATEGORIES:Conferences - Seminars
DESCRIPTION:Ms Ying Zhang\, McGill University\nAbstract: Data-driven manuf
 acturing is an approach to leverage data across the product lifecycle into
  manufacturing intelligence to guide decision-making. It enables manufactu
 rers and designers to make better decisions to reduce costs and increase e
 fficiency.  This talk aims to present an application of data-driven analy
 sis 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 i
 s to determine the manufacturability of the given design. To fill this gap
 \, an investigation of using the machine learning (ML) method to assess th
 e manufacturability of designs for AM processes is carried out. A web-base
 d tool as the final delivery can serve as a first-level evaluation of desi
 gns for novice AM users to reduce the waste of time and cost in AM fabrica
 tions. Specific challenges associated with ML-assisted applications in des
 ign and manufacturing and roadblocks towards data-driven manufacturing wil
 l be also discussed.\n\nBio: Ying Zhang is a Ph.D. candidate at McGill Uni
 versity in Canada supervised by Professor Yaoyao Fiona Zhao. Ying has subm
 itted her initial thesis and is on the track to graduation. Her current re
 search projects focus on data-driven approaches in additive manufacturing 
 applications. Prior to her relocation to Canada in 2018\, she had been a s
 oftware and process engineer for almost two years in China. Moreover\, Yin
 g 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.
LOCATION:https://epfl.zoom.us/j/68215757894
STATUS:CONFIRMED
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