Combining fuzzy rule induction, expert knowledge and physical laws for modelling emerging complex manufacturing processes

Needs and challenges: The successful integration of emerging machining processes into industry requires a good understanding of their capabilities. However this can be a lengthy process as precise physical laws are often missing. Thus, knowledge on the process is often brought incrementally by both accumulation of empirical results and discovery of some of the process fundamental laws. Many modelling approachs exist but one that could combine knowledge extracted from experimental data, machine operator expertise and physical laws, in order to accurately predict machining process behaviours, is not easily implemented.

The main aim of the proposed research is to develop a standard modelling approach based on fuzzy logic for integrating these three sources of knowledge. As a case study and to support the development of the modelling approach, the emerging micro Electro Discharge Machining (μEDM) process will be investigated.

Data will be collected using in house state of the art equipments (μEDM machines, metrology etc), using university researchers expertise in EDM and machine tool manufacturers expertise.

During this PhD you would be required to undertake high quality research within the theme of Intelligent and knowledge based systems and Micro/nano manufacturing. You will be required to present the results of your research through publications and presentations at seminars, conferences and other events.

Informal enquiries may be made to Dr Samuel Bigot – [Email Address Removed]. For further information about Cardiff School of Engineering and the Institute of Mechanical and Manufacturing Engineering, see http://www.engin.cf.ac.uk/research/resInstitute.asp?InstNo=15

The successful candidate will need to have an academic grounding in Engineering (Manufacturing Engineering or computer science), a first-class or 2.1 Honours degree, and experience in C++ programming. Candidates whose first language is not English will need to demonstrate proficiency in the English language (IELTS 6.5 or TOEFL 600).

When applying please state the name of the supervisor(s) in the "prospective supervisor" section of the application.