Improving performance of defect detection by setting skewed tolerance and joint tolerances in crimp force monitor

Abstract

A Crimp Force Monitor (CFM) detects defects by whether the crimp force curve of the force sensor exceeds the set tolerance, with the goal of low defect miss rate and false alarm rate. In this study, typical defects made by hand are crimped with an automatic crimping machine together with good products to obtain continuous data of the crimping force curves and to process the data. For the peak and area deviations of the crimp force curve, the good products show skew‐normal distribution, and the defective samples show outliers and different deviation intensities in the positive and negative directions. Furthermore, by manually intervening in the batch production of multiple groups of defects and comparing the defect miss rate and false alarm rate of CFM with different tolerance settings, the peak skewed tolerance, joint loose tolerance and joint skewed tolerance tree settings can meet a low defect miss rate and low false alarm rate at the same time. The group test results verify the skew‐normal distribution of crimping force curve deviation rate and the characteristics of deviation intensities, providing reference for the tolerance setting of CFM in automated terminal crimping production.