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SUMMARY:Predictive Manufacturing: Statistical Data mining for manufacturin
 g data - ABDUL RAUF KHAN  PhD Fellow\, Automation and Control Departmet of
  Electronic Systems\, Aalborg University\, Denmark
DTSTART:20161128T150000Z
DTEND:20161128T160000Z
UID:TALK69129@talks.cam.ac.uk
CONTACT:Philip Woodall
DESCRIPTION:In today’s manufacturing paradigm predictive capabilities in
  manufacturing can be considered as strategic advantage over the competito
 rs. Due to the technological advancement and globalization of world’s ec
 onomy\, manufacturing industry is going through a transitional phase with 
 an unprecedented pace. Digitalization of manufacturing\, Industrial intern
 et of things (IIOT) and fourth industrial revolution are the concepts that
  are getting monumental attention throughout the industry. The essence of 
 these concepts is not only the connection between machines but an idea of 
 smart or more informed and automated decision making. In this talk I will 
 discuss a strategy to deal with sensory data with an aim to improve indust
 rial quality control. The core idea is to implement a systematic approach 
 to analyze sensor outputs from different quality control stages and extrac
 t an insight that leads towards the more informative decision making.
LOCATION:Seminar room 1\, Institute for Manufacturing\, Cambridge
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