A more complete solution to the machining economics problem is one that takes into account several constraints of the actual machining operation. The object of the paper is to illustrate how a relatively new mathematical programming method called geometric programming can be used to determine the optimum machining conditions when the solution is restricted by one or more inequality constraints. This optimizing method is especially effective in machining economics problems, where the constraints may be nonlinear and the objective function of more than second degree. Furthermore, the geometric programming approach furnishes a unique insight into how the optimizing criterion is distributed among its components for a given set of input parameter values.