Predictive Manufacturing: Statistical Data mining for manufacturing data

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• ABDUL RAUF KHAN PhD Fellow, Automation and Control Departmet of Electronic Systems, Aalborg University, Denmark
• Monday 28 November 2016, 15:00-16:00
• Seminar room 1, Institute for Manufacturing, Cambridge.

If you have a question about this talk, please contact Philip Woodall.

In today’s manufacturing paradigm predictive capabilities in manufacturing can be considered as strategic advantage over the competitors. Due to the technological advancement and globalization of world’s economy, manufacturing industry is going through a transitional phase with an unprecedented pace. Digitalization of manufacturing, Industrial internet 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 industrial quality control. The core idea is to implement a systematic approach to analyze sensor outputs from different quality control stages and extract an insight that leads towards the more informative decision making.

This talk is part of the DIAL seminars series.

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