Novel AI Techniques in Dealing with Manufacturing Variations for Automobile Assembly Systems

Academic Institution: University of Strathclyde

Academic Supervisor: Professor Xiu Yan

Industry Partner: PSA Group (Peugeot)

PhD Student: TBC

Start Date: April - July 2019

Abstract

The project is proposed by the SMeSTech Lab of the University of Strathclyde, working in partnership with PSA (Peugeot), France. The SMeSTech Lab is well positioned to advance research and development of mechatronic solutions for space applications and their terrestrial exploitation.

This project aims to derive a generic and integrated system in which the variations in the parts manufactured in an automobile assembly process can be detected and assembly operations improve using the new AI algorithm. This is further used to drive a manipulator such as a robot for intelligent intervention. The algorithm exploits the state-of-the-art techniques of machine learning as the most outstanding AI technique so far. The challenges lie in training and recognising the features with very tiny differences using a machine learning algorithm and generate an optimised algorithm for the robot to make optimised assembly.

PSA Group has shown its great interest in collaboration in this project. The project could bring intelligence into the modern automobile industry and improve the performances of manufactured vehicles, especially those high ranking limos.


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