A genetic algorithm for assessing flatness in automated manufacturing systems
The measurement of flatness for manufactured parts is one of the most frequently used procedures in automated manufacturing systems. Measuring instruments are commonly utilized in taking measurement data from manufactured surfaces for inspection purposes. The measurement data is then used to evaluate the geometric information, from errors associated with its surface. The study proposes the computational approaches for flatness with respect to ASME Y14.5M-1994 standard. The proposed methods consider the trade-off between the accuracy of flatness and the efficiency of inspection. Two approaches of computational metrology based on genetic algorithms are proposed to explore the optimality of flatness measurement and the flatness feasibility analysis. The results show that the optimization algorithms provide exact flatness errors and adequate tolerance size.
genetic algorithms flatness tolerance minimum zone flatness non-linear programs