An optimal localization of blank part in NC machining

The blank of the aviation complex part is usually produced by casting or forging, which results in a bad stock allowance distribution. Even small deviations in the blank parts or slight inadequacy in fixturing may result in a local shortage of material. Thus, the localization of blank is important in the numerical control (NC) machining process. However, except for a positive allowance, other actual requirements such as the efficiency of rough machining are not considered in most existing optimal models of localization. In this paper, we formulated the blank part localization problem as a combined problem of minimum allowance and demand function. The new unconstrained optimal model aims to achieve extra actual requirements based on a positive allowance distribution by adjusting the demand function to achieve an even allowance distribution or improving the efficiency of rough machining. Improving the efficiency of rough machining by seeking an optimal localization is first presented in the paper. The optimal model is solved by the particle swarm optimization (PSO) algorithm, and the localization result is compared with others of existing optimal models. Experiment results show that the optimal model proposed is appropriate and feasible to achieve extra requirements besides a positive allowance.