Maximum likelihood estimation of probability for impact Resistance of safety guards

The article examines the testing method described in Annex B of the ISO 14120 standard for assessing the impact resistance of machine guards. The typical testing practice involves firing a single shot from a ballistic cannon at the guard, with sensors measuring the projectile's velocity before and after impact. However, meeting the guidelines for this test presents challenges, including the difficulty of identifying and hitting the "weakest point" of the guard and ensuring the projectile strikes the surface in a perpendicular manner. The key findings, derived from a five-year collaboration between two research institutions, focus on analyzing uncertainties inherent in these standardized testing methods. Two statistical distributions, Logistic and Gaussian, are employed to process the data. The traditional approach of creating a histogram before calculating the cumulative distribution function (CDF) was found inadequate because it reduces the number of data points available for accurate curve fitting. To improve this process, the Probit method, already used in the AEP 2920-2016 standard, is introduced as a more effective regression technique for the Gaussian distribution. A comparison is made between results from different regressions, focusing on discrepancies in the tails of the curves, where the divergence between models becomes more significant. The article also discusses methods for estimating the statistical dispersion of test results. Specific examples of trials carried out at the INAIL laboratories in Monte Porzio Catone are provided, showing the application of these methods in practice. These experiments were part of a joint research initiative between the University of Perugia and the Department of Technological Innovations and Safety of Plants, Products, and Anthropic Settlements (DIT). By presenting this research, the article seeks to address the practical limitations of standardized tests and suggests alternative methods to improve accuracy and reliability of machine guard impact resistance evaluations.