This paper is concerned with optimization of the surface roughness when milling Mould Aluminium alloys (AA6061-T6) with carbide coated inserts. Optimization of milling is very useful to reduce cost and time for machining mould. The approach is based on Response Surface Method (RSM) and Radian Basis Function Network (RBFN). RBFN was successfully used by Tsoa and Hocheng in their recent research. They used this network to predict thrust force and surface roughness in drilling. In this work, the

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... jectives are to find the optimized parameters, and to find out the most dominant variables (cutting speed, federate, axial depth and radial depth). The optimized value has been used to develop a blow mould. The first order model and RBFN indicates that the feedrate is the most significant factors effecting surface roughness. RBFN predict surface roughness more accurately compared to RSM.