Time sensitive networking for Industrial Internet of Things
Award Details: Self-funded
Duration: Full Time - 3 years 6 months fixed term
Application deadline: This opportunity will only remain open until a suitable candidate is identified- early application is therefore advised. Standard University research application closing dates apply.
Informal enquiries are essential before application; contact Dr. Xingang Wang on firstname.lastname@example.org or Prof. Weidong Li on email@example.com.
Congratulations on taking your first steps toward a Research Degree with Coventry’s Faculty of Engineering, Environment and Computing. As an ambitious and innovative University, we’re investing an initial £100m into our new research strategy, ‘Excellence with Impact’. Through original approaches from world-leading experts, we’re aiming for our research to make a tangible difference to the way we live. As a research student you are an integral part of Coventry’s lively and diverse research community and contribute to our reputation for excellence. With our exceptional facilities and superb support mechanisms you are afforded every opportunity for academic success.
Today’s industrial network implementation is static and application-specific that requires high engineering effort. Industry 4.0 is believed to be the next evolution step for future manufacturing and this trend sets new requirements to industrial networks.
The machine data streams need deterministic delay, real time communication and extraordinarily low packet loss. Deterministic delay is critical to meet the control loop frequency requirements and low packet loss is needed to protect machine to operate safely. The general purpose best effort Ethernet cannot meet these requirements for industrial critical data streams. Initiatives and standards such as Time Sensitive Networking (TSN) aim to provide solution definition and universal standards to address these challenges. As the TSN standards are being partially defined, there are still many open questions to be investigated.
One vision for future industrial TSN network is to incorporate Software Defined Networking (SDN) approach to provide innovative Quality of Service (QoS) algorithms and simplify the deployment of new forwarding strategies for specific applications.
about the centre/department
The Institute for Advanced Manufacturing and Engineering (AME) is a £32m+ collaboration between Coventry University and Unipart Manufacturing. This project is supported by the Higher Education Funding Council for England’s Catalyst Fund.
AME is has introduced and realised a bespoke ‘Faculty on the Factory Floor’ at Unipart Powertrain Applications company site in the heart of Coventry. This forms the focal point of activity and has state-of-the-art robotic automation, forming, joining, analysis and simulation, metrology and product verification technology.
Successful applicants will have:
- A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average, or
- A Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at merit level (60%).
- The potential to engage in innovative research and to complete the PhD within a prescribed period of study
- Language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component).
Additionally, the successful candidate will have strong computer software development skills (which will be skills tested on application) as well as experience in one or more of the following areas:
- Software defined networking
- Programming skills
- Networking skills
- Understanding of the manufacturing environment and processes
Eligibility & Application Procedure
All UK/EU/International students are eligible to apply that meet the academic requirements, the eligibility criteria can be found making an application page.