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An intelligent approach for the prediction of surface roughness in ball-end machining of polypropylene

This paper describes a new predictive model based on genetic algorithms for determining the optimised manufacturing parameters for ball-nose machining of sculptured surface polypropylene products. This was an invited paper to the RCIM journal selected from the international conference FAIM2007 (USA). The research provides a new means to predict surface roughness for polypropylene machined parts. This work was part of a £420k EPSRC research programme (GR/R67507/01) at the University of Bath entitled 'CRYMAN-Rapid manufacture of soft flexible materials for customised shoes'. The results have led to an industrially funded studentship with Renishaw plc to investigate machining and modelling techniques.