Next Generation Aircraft Digitally Enhanced Hybrid Material Joint Assembly
Lead Research Organisation:
University of Nottingham
Department Name: Faculty of Engineering
Abstract
Traditional aircraft manufacture can be expensive and slow. Typically, novel manufacturing techniques aim to reduce production costs and time, improve product quality, and enable automation. However, technical challenges still need to be solved before these processes are capable of meeting engineering requirements and being deployed on an industrial scale.
The key aim of this PhD is to establish how a specific novel manufacturing technique can be implemented to achieve the greatest positive impact
on cost, quality, and time. This includes:
Identifing and challenging the state of the art in existing manufacturing processes for assembling aircraft structures;
Establishing and characterising:
The relationship between different process parameters and how they contribute to the achievement of engineering requirements;
The relationship between out-of-tolerance manufacturing processes and the structural integrity of hybrid (CFRP, aluminium, titanium) material joints;
Develop a data analytics approach for managing process control and optimising manufacturing processes, utilising data captured and fed
back from industrial equipment e.g. drilling machines.
The key aim of this PhD is to establish how a specific novel manufacturing technique can be implemented to achieve the greatest positive impact
on cost, quality, and time. This includes:
Identifing and challenging the state of the art in existing manufacturing processes for assembling aircraft structures;
Establishing and characterising:
The relationship between different process parameters and how they contribute to the achievement of engineering requirements;
The relationship between out-of-tolerance manufacturing processes and the structural integrity of hybrid (CFRP, aluminium, titanium) material joints;
Develop a data analytics approach for managing process control and optimising manufacturing processes, utilising data captured and fed
back from industrial equipment e.g. drilling machines.
People |
ORCID iD |
Benjamin Pamplin (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/W52220X/1 | 01/10/2021 | 30/09/2026 | |||
2754542 | Studentship | EP/W52220X/1 | 01/10/2022 | 30/09/2026 | Benjamin Pamplin |