MACHINE LEARNING-BASED ALGORITHM FOR CIRCULARITY ANALYSIS
Keywords:
Key words. circularity analysis, pistons, gears, , a coordinate measuring machine (CMM).Abstract
Abstract. A crucial component of quality control in industrial processes is circularity analysis. It refers to the measuring of an object's roundness or circularity, which is crucial for making sure the product fits and performs as intended. Precision parts like pistons, gears, and bearings are frequently made using circularity analysis. Comparing an object's real form to its ideal circular shape is a common method for determining how circular it is. Usually, a coordinate measuring machine (CMM) or a laser scanner are used for this comparison. The circularity of the object is then ascertained by analysis of the measurement data.
References
"Detecting and Correcting for Label Shift with Black Box Predictors" by Kira Selby, Sanmi Koyejo, and David Dunson, published in the Proceedings of the 36th International Conference on Machine Learning in 2019.
"Coordinate Measuring Machines and Systems" by Robert J. Hocken, published by Springer in 2015.
"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron, published by O'Reilly Media in 2019.
"Receiver Operating Characteristic (ROC) Curve for Medical Diagnostic Test Evaluation" by Jason H. Moore and Yongsheng Huang, published in the Journal of Clinical Epidemiology in 2004.
"Human-in-the-Loop Machine Learning" by Robert R. Hoffman, published in the Journal of Cognitive Engineering and Decision Making in 2018.
