23/07/2018

PhD in Engineering: Machine learning techniques for the optimisation and simulation of Metal Additive Layer Manufacturing process chains

uložit do oblíbených

  • název organizace
    Cardiff University
  • ZEMĚ PŮVODU ORGANIZACE
    United Kingdom
  • TYP FINANCOVÁNÍ
    Funding
  • termín uzávěrky
    01/10/2018
  • OBLAST VÝZKUMU
    Professions and applied sciences
  • STÁDIUM KARIÉRY
    First Stage Researcher (R1) (Up to the point of PhD)

Project Description

The aim of this PhD is to develop new data analytic tools (eg machine learning, data mining) to support the understanding, the optimisation and the multi-scale and multi-physics simulation of metal additive layer machining (ALM) process chains.

These data analytics tools should meet the needs of the H2020 funded project MANUELA. In particular, to develop 'intelligent' feedback loops enabling 'online' manufacturing optimisation, design optimisation and tuning of multi-scale and multi-physics models used for simulations and for the implementation of accurate digital twins of the investigated pilot lines.

Depending on the type of data available (eg temperature maps, machining parameters, localised acoustic information) and on the available controllable factors, various types of process modelling approaches could be used to extract knowledge and features.

State of the art modeling, data mining and machine learning tools will be reviewed (eg techniques for data regression/classification/clustering such as deep neural network, support vector machine, and dimension reduction learning models, as well as image processing algorithms) and the most relevant will be implemented and enhanced to meet the demands of real data collected at different stages of the pilot line.

To find out more information on how to apply please visit our website:

https://www.cardiff.ac.uk/study/postgraduate/funding/view/phd-in-enginee...