Efficient Genetic Algorithms for Measurement of Flatness Error and Development of Flatness Plane Based on Minimum Zone Method

Abstract

Measurement of geometrical tolerances is one of the prime processes in manufacturing for ensuring the quality of the machined components. Manufactured components are sent to assembly line based on measurement reports, so measurement is inevitable in any production setup. Flatness error is one of the important icons in the crew of geometrical tolerances; if unqualified components are sent to assembly line, the components may not function according to the design requirements. This paper presents real coded efficient genetic algorithms (EGA) for flatness error measurement and flatness plane development using minimum zone method. Flatness plane has been developed by determining the flatness plane coefficients. The flatness plane coefficients determine the orientation of the surface. The proposed algorithms are equipped with high precision, accuracy, good repeatability and fast mature convergence rate. The algorithms characteristics like precision, accuracy, repeatability ensure the reliability of measurement results of measured component and fast mature convergence rate ensure the reduction in the inspection time.