### Multi-objective optimization of multipass turning processes

Abstract

In this paper, a methodology is proposed for the multi-objective optimization
of a multipass turning process. A real-parameter genetic algorithm (RGA) is
used for minimizing the production time, which provides a nearly optimum
solution. This solution is taken as the initial guess for a sequential quadratic
programming (SQP) code, which further improves the solution. Thereafter,
the Pareto-optimal solutions are generated without using the cost data. For
any Pareto-optimal solution, the cost of production can be calculated at a higher
level for known cost data. An objective method based on the linear programming
model is proposed for choosing the best among the Pareto-optimal solutions. The
entire methodology is demonstrated with the help of an example. The optimization
is carried out with equal depths of cut for roughing passes. A simple numerical method
has been suggested for estimating the expected improvement in the optimum solution
if an unequal depth of cut strategy would have been employed.