Due to the non-deterministic nature of process sequence design for multi-st
age cold forging, various process designs are available depending on the in
itial billet geometry and the order of basic processes such as forward/back
ward extrusion, upsetting and trimming process. Therefore, various process
sequences Should be determined and compared to obtain an optimal solution.
For this purpose, a depth-first search. a searching technique used in artif
icial intelligence, has been introduced in developing an expert system for
multi-stage cold forging process design. As a result, process designers can
select the optimal process sequence from the searched feasible solutions b
y estimating the values of evaluation functions that are introduced to repr
esent the important design characteristics. In the present investigation, t
he distributions of the global effective strains in the final product and t
he forming loads required at each forging stage were selected to be control
led. In general, a more realistic process sequence should be determined by
taking into account manufacturing conditions such as the number of forming
stages, the forming loads, the shearing diameter of the coil, the open upse
tting diameter, and the knock-out lengths of the die and punch. In this pap
er, a methodology of applying the searching technique for process sequence
design is discussed, and the flexibility of the introduced searching techni
que is evaluated by generating design examples of a shaft part, a wrench an
d hexagonal bolts of AISI 1045. (C) 1999 Elsevier Science S.A. All rights r
eserved.