PhD Studentship: Implementing real time online Artificial Intelligence in process

Cranfield University

Application deadline: 07/09/2018
Start date:   24/09/2018
Fee status of eligible applicants: UK only
Duration 3 years

Supervisors- 1st : Dr Peter Clough    2nd: Prof Vasilije Manovic

Sponsored by: Sponsored by EPSRC through Doctoral Training Partnership Funding, this studentship will provide a bursary of £14,777 (tax free) plus full fees for three years.              

The research question to be investigated: Can the implementation of real-time online Artificial Intelligence (AI) in process engineering lead to improved reactor control relative to non-AI control?

This student-lead project will investigate hybrid-AI models for the development and application of AI for process operation prediction and bench-scale reactor control automation, which if applied at an industrial scale could lead to: 1) Safer operation, 2)      Improved product yields, 3) Reduced reactor downtime, and 4) And economic gains from all the above.

The research question will be addressed by the student over the course of their PhD by answering the following three specific objectives:

  1. Using hybrid AI methods, develop an online, real-time AI model that is capable of predicting the response of the reactor under steady state, and dynamic changes in operating conditions during the calcination of limestone (a stage in cement manufacturing and the calcium looping process).
  2. Implement the AI model in the process of calcium oxide carbonation (the reverse of the calcination), in doing so implement changes to the code to improve the models learning adaptability, speed and accuracy.
  3. Connect the AI model to specific reactor input control hardware and facilitate the models learning when controlling this hardware.

There is great potential for AI technology at an industrial scale and the work conducted here, at the bench scale, is a significant precursor for its future deployment. The future impact of AI in all industries, including the process industry, will be significant and cannot be understated, it is important that fundamental research like this is conducted so that the technological advancements in AI can be deployed at scale in this new field.

Furthermore, this project is expected to deliver several high-impact publications and will influence the direction of future grant proposals.

Funding is available for the student to attend international conferences and network meetings. In addition, training on specific software and reactor operations can be provided as required.

It is expected that the student will publish at least 3 academic journal papers, attend 4 international and national conferences and will gain a multitude of transferable skills throughout their PhD. PhD’s are widely recognised as being key qualifications for future employment in areas including academia, consultancy, higher-level management in industry, and research and development.

Entry requirements

First or an upper second class UK honours degree or equivalent in Chemical Engineering, Process Engineering, Environmental Engineering, Software Engineering, Artificial Intelligence, Computer Systems Engineering, Computer Science, or another similar course.

Funding

To be eligible for this funding, applicants must be a UK national.

How to apply

For further information: Dr Peter Clough

Email: p.t.clough@cranfield.ac.uk
T:
(0) 1234 750111 Ext: 4873

If you are eligible to apply for this studentship, please complete the online application form.

For information about applications
Admissions
T: +44 (0)1234 758082
E: studyenergy@cranfield.ac.uk

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Type / Role:

PhD

Location(s):

South East England