Optimization of machining datum selection and machining tolerance allocation with genetic algorithms

In machining process planning, selection of machining datum and allocation of machining tolerances are crucial as they directly affect the part qualit y and machining efficiency. This study explores the feasibility to build a mathematical model for computer aided process planning (CAPP) to find the o ptimal machining datum set and machining tolerances simultaneously for rota tional parts. Tolerance chart and an efficient dimension chain tracing meth od are utilized to establish the relationship between machining datums and tolerances. A mixed-discrete nonlinear optimization model is formulated wit h the manufacturing cost as the objective function and blueprint tolerances and machine tool capabilities as constraints. A directed random search met hod, genetic algorithm (GA), is used to find optimum solutions. The computa tional results indicate that the proposed methodology is capable and robust in finding the optimal machining datum set and tolerances. The proposed mo del and solution procedure can be used as a building block for computer aut omated process planning.