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[Roy, Rajkumar]

Development of a Soft Computing Approach to Predict Roll Life in Long
Product Rolling


Industry CASE Studentship at Cranfield University
Proposed by: Dr. Rajkumar Roy, Cranfield University
Industrial Sponsor: Corus UK
November 2004 - October 2007

Outline of the Project

Rolls are estimated to contribute about 5-15% of overall production
costs in long product rolling. Roll life in long product rolling is
dependent on the rate of wear of the rolls. Any prediction about the
roll life will require an understanding of the roll wear mechanisms and
a model for the wear. It is observed that after many years of research,
scientists and engineers are still working on developing such a model.
On the other hand expert operators on the shop floor often take
corrective actions to improve roll life. Through experience they have
developed a mental model of the roll wear behaviour and therefore the
roll life. In absence of quantitative model for the roll wear and the
roll life predictions, it is proposed that this research will develop an
approach utilizing Soft Computing techniques (Neural Networks and Fuzzy
Logic) to predict roll life for long product rolling. Soft Computing
techniques are proven in many domains to be successful in modeling a
complex environment using empirical data and human expertise.

It is expected that the research will utilize historical data available
within the industry to establish any relationship between certain key
roll, component and production variables (quantitative) and actual life
of the roll. Neural networks and statistical approaches can be used at
this stage of the research. In parallel the research will investigate
how expert operators adjusts machine and roll parameters to improve roll
life. This would involve extensive knowledge capture exercise. It is
expected that fuzzy logic based representation will allow the knowledge
to be made explicit. The fuzzy model will incorporate qualitative
variables involved in the roll life prediction. The third phase of the
research will focus on integrating the quantitative and qualitative
models to develop a complete model for roll life prediction.

EPSRC is expected to pay tuition fees to Cranfield. The student would
receive around 11K pounds sterling tax-free per annum for the three
years. Interested graduate/postgraduate students with
manufacturing/mechanical engineering background are invited to submit
their CV for an informal discussion over telephone or email. Additional
background in knowledge capture and Soft Computing will be beneficial.
The minimum academic requirement for entrants to the degree is an upper
second class honours degree or its equivalent. Please note that the
funding is restricted to British Nationals, in special cases it may be
offered to an EC national.

Please respond by 30th Nov. 2004.

For informal enquiries and application (detailed CV), please contact:
Dr. Rajkumar Roy at your earliest:

Dr. Rajkumar Roy
Senior Lecturer and
Course Director, IT for Product Realisation
Department of Enterprise Integration,
School of Industrial and Manufacturing Science,
Cranfield University,
Cranfield, Bedford,
MK43 0AL, United Kingdom.
Tel: +44 (0)1234 754072 or +44 (0)1234 750111 Ext. 2423
Fax: +44 (0)1234 750852
Email: r.roy at cranfield.ac.uk or r.roy at ieee.org
URL: http://www.cranfield.ac.uk/sims/staff/royr.htm
http://www.cranfield.ac.uk/sims/cim/people/roy.htm