Automated Generative Manufacturing Process Design, Feasibility, Planning and Assessment(EPSRCICASE award with JLR)

Lead Research Organisation: University of Sheffield
Department Name: Automatic Control and Systems Eng

Abstract

This research project aims to improve the design and manufacturing process for car bodies. We want to create a system that automatically checks if the available robots can do the job and if the parts can be put together successfully. This will save time and effort compared to the current method, where engineers manually check each step. Our system will also be able to quickly test and compare different assembly sequences to find the best one for reducing cost and increasing efficiency. Once we have developed this system, it can be used in the production process to make building car bodies faster and more efficient.

As a PhD student at the University of Sheffield, you will have access to world-class facilities and expert supervision from leading researchers in the field. You will have the opportunity to work on real-world problems and challenges faced by Jaguar Land Rover, and to develop your skills and expertise in digital manufacturing.

In addition to receiving a full funding package, including a competitive stipend and support for travel and research expenses, the successful candidate will also have the opportunity to gain valuable industrial experience through working closely with Jaguar Land Rover. Upon completion of the PhD, there will be opportunities for employment as an academic researcher or as an industrial researcher at Jaguar Land Rover.

This is a unique and exciting opportunity to be at the forefront of research in digital manufacturing, and to develop your career in this rapidly-growing field. If you are a highly-motivated individual with a background in computer science, engineering, or a related field, we encourage you to apply for this funded PhD position at the University of Sheffield and Jaguar Land Rover. Don't miss out on this opportunity - apply now!

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/X524980/1 01/10/2022 30/11/2027
2898320 Studentship EP/X524980/1 01/12/2023 30/11/2027 Richard Padden