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Artificial Intelligence (AI) has been gaining popularity since the 1960s. Expert Systems (ES) within artificial intelligence are now being applied to industrial and manufacturing areas as a means of solving problems and as decision making aids. Expert systems provide a way to capture expert knowledge so mat it is not permanently lost. With the stiff competition in the world market, the tendency is leaning toward manufacturing the part with control of several parameters especially from the point of view of conserving material and money. Powder metallurgy is a metalworking process for forming precision metal and nonmetal components and shapes from particulate matters. The main reason for this fast advancing technology is that it is an economical, high-volume production method for making parts almost to the final dimensions and finishing them with little or no machining operations.

In recent years, P/M techniques have been combined with conventional deformation processes to manufacture various engineering products. During the forging of a metal powder preform, changes in volume and density occur, and the various theoretical analyses developed based on volume constancy cannot be applied to the deformation of porous materials. The paper reviews some of the work carried out in chronological order. A mathematical solution was developed for axisymmetric forging of iron powder preforms (solid and hollow) under the frictional conditions based on the yield criteria proposed by Tabata and Masaki for porous materials. The theoretical values agreed with experimental values within accuracy (85-95%).