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Time Series Anomaly Detection in Batch Semiconductor Processes using Localised Reconstruction Errors from Semi-Supervised Convolutional AutoEncoders deployed as a Containerised Microservices Edge Solution

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Original languageEnglish
Title of host publication20th European Advanced Process Control and Manufacturing Conference
Subtitle of host publicationAPCM Europe
Place of PublicationToulon
Edition20th
Publication statusPublished (in print/issue) - 5 Apr 2021
Event20th European advanced process control and manufacturing (apc|m) Conference - Toulon, France
Duration: 30 Mar 20201 Apr 2020

Conference

Conference20th European advanced process control and manufacturing (apc|m) Conference
Country/TerritoryFrance
CityToulon
Period30/03/201/04/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Deep learning
  • Autoencoder
  • Time Series
  • Semiconductor
  • Manufacturing
  • Reconstruction Error

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