A better characterization of the stress state of each

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Unformatted text preview: f generations, number of populations in each generation, crossover rate, mutation rate, fitness functions, penalty functions have significant impact on it performance. Determination of those numbers could be a optimization problem. In this research, a set of parameter have been chosen as follows. Generation =20; population =50; crossover rate=0.6; mutation rate=0.1; linear function for fitness evaluation; use maximum possible machining cost as penalty function, which is determined by assigning lowest IT grades to all features. Parameters for Monte Carlo simulation in stack up analysis module are the same as described in [Song et al., 2005]. The same prismatic workpiece as in section 4 is employed. Table VII lists the optimal result along with the sensitivity analysis based assignment plan. Approach Sensitivity based GA based Setup 1 P1 P2 9 5 9 6 P3 9 9 Setup 2 P4 P5 9 6 8 7/8 P6 6 6 Setup 3 P7 P8 9 9 9 9 Setup 4 P9 P10 7 6 8/9 5 Table VII; Comparison of assignment results. Tolerance Assignment for Production Planning 223 It can be concluded t...
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