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A New Data Analytics Framework Emphasising Pre-processing in Learning AI Models for Complex Manufacturing Systems

  • Caoimhe M. CarberyEmail author
  • Roger Woods
  • Adele H. Marshall
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 924)

Abstract

Recent emphasis has been placed on improving the processes in manufacturing by employing early detection or fault prediction within production lines. Whilst companies are increasingly including sensors to record observations and measurements, this brings challenges in interpretation as standard approaches for artificial intelligence (AI) do not highlight the presence of unknown relationships. To address this, we propose a new data analytics framework for predicting faults in a large-scale manufacturing system and validate it using a publicly available Bosch manufacturing dataset with a focus on pre-processing of the data.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Caoimhe M. Carbery
    • 1
    • 2
    Email author
  • Roger Woods
    • 1
  • Adele H. Marshall
    • 2
  1. 1.Electronic Computer EngineeringQueen’s University BelfastBelfastUK
  2. 2.Mathematical Sciences Research CentreQueen’s University BelfastBelfastUK

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