  This paper presents an optimization technique for the multi-pass face milling
process. Genetic algorithm (GA) is used to obtain the optimum cutting
parameters by minimizing the unit production cost for a given amount of
material removal. Cutting speed, feed and depth of cut for the finish and rough
passes are the cutting parameters. An equal depth of cut for roughing passes
has been considered. A lookup table containing the feasible combinations of
depth of cut in finish and rough passes is generated so as to reduce the number
of variables by one. The resulting mixed integer nonlinear optimization problem
is solved in a single step using GA. The entire technique is demonstrated in a
case study. Post optimality analysis of the example problem is done to develop
a strategy for optimizing without running GA again for different values of
total depth of cut.
