Knowledge Management and Diagnostics - PhD Studentship

Cranfield University - Manufacturing

Start Date: ASAP
Eligibility: UK, EU
Duration of award: 3 years 
Supervisors: Professor Ian Jennions, Dr Zakwan Skaf

Sponsored by The Boeing Company this studentship will provide a bursary of up to £20,000 p.a. (tax free) plus fees* for three years for the right candidate.

Knowledge Management is a problem for industry. It should be a continuous process in which knowledge is captured as it is created, or at least at the completion of major projects, but this is seldom the case. It only really comes to light when older engineers retire and this gives an impetus to the company to retain some of the knowledge, often too little too late. When this is applied to the field of IVHM (Integrated Vehicle Health Management) we are typically considering experimental data, algorithms, reports and technical supporting documents. How to arrange all of this knowledge in a repository that is searchable and useful in practice is a challenge. This PhD will consider the problem from two sides. The first is how to organize and manage projects in a KMS that satisfies the needs of the Centre and industry, but then also to test the proposed methodology by writing diagnostic algorithms, documenting them and inserting them into the KMS.

Consequently, the objectives of the project are:

  • Given requirements for a KMS derived a meaningful structure
  • Populate the structure with information surrounding the project
  • Check that this satisfies the needs of industry, i.e. if I have a problem and a certain amount of data, what method do I use?
  • Write diagnostic algorithms, on available data, and test KMS
  • Recommend further work / improvements

As a part of working in this industrially sponsored project, the student will work in close collaboration with Boeing. He/she will need to present their research findings regularly to the project team.

Entry requirements:
Applicants should have a first or second class UK honours degree or equivalent in a related discipline, such as engineering or computer science. The ideal candidate should have some understanding of the areas of knowledge management and/or algorithms for signal analysis, along with a desire to work in this exciting area. The candidate should be self-motivated, and have good communication skills for regular interaction with other stakeholders.

* To be eligible for this funding you must be a UK or EU national.

 How to apply:
For further information please contact: Dr Zakwan Skaf, E:, T: (0) 1234 750111 xtn 2324. If you are eligible to apply for this research studentship, please complete the online application form

For further information contact us today:
T: 44 (0)1234 758008

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