A Novel Iterative Field Search Approach to Minimum Zone Circle for Roundness Error Estimation

Abstract

Abstract Roundness is one of the common attributes in the manufacturing industry. Roundness is the most prominent of the extant fundamental forms, as the majority of the fabricated components are round or cylindrical. The examination of roundness error associated with such features is critical since inadequate evaluation might result in the rejection of excellent parts. The performance of any equipment depends on the mating parts. Out-of-roundness components cause the inefficiency of such equipment’s system performance. As a result, roundness error assessment is critical for macro-sized specimens as well as for micro- and nano-sized components. The present article proposes a novel approach to Minimum Zone Circle (MZC) to evaluate the roundness error. An iterative field search methodology is used in the suggested approach. The proposed methodology evaluates the roundness error based on the generated discretized points within the search space and continues the same by decreasing the search space with an increase in the number of iterations to attain the Minimum Zone Error (MZE). The proposed algorithm has been tested with ten CMM (coordinate measuring machine) datasets and ten form datasets available in the literature studies and found to be excellent in comparison to the existing techniques. Further, the proposed methodology was also implemented to estimate the MZE of centerless ground specimens at multiple cross sections, and the roundness error obtained was lesser as compared to the LSC, MCC, and MIC. The number of generated discretized points is flexible and can be varied to reduce the number of iterations and computations. The recommended method is quite effective in assessing the roundness error when compared to the existing techniques. It also works well on data that was both evenly and unevenly spaced. The results suggest that altering the search field area for higher computing efficiency is straightforward, resilient, and versatile.