Automation of Quality Control in the Automotive Industry using Deep Learning Algorithms

Abstract

International audience<div style=""&gt<font face="arial, helvetica"&gt<span style="font-size: 13px;"&gtQuality control is an essential operation for an&nbsp;</span&gt</font&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtautomotive company like Faurecia. A vast number of references&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtis produced, and many regions of interest need to be checked.&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtFor that, quality control is necessary and should be applied&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtto every reference part. Visual inspection is achieved by the&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtoperator who checks each part manually. After several checks per&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtday, the operator gets tired and thus may misqualify a welding&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtseam or a component control. To avoid that, Faurecia is trying&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtto integrate automatic quality control to obtain better overall&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtequipment effectiveness (OEE), especially to avoid performance&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtdegradation over the operator’s shift. Researches demonstrate the&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtability of a neural network to reach high precision in detecting&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtobject presence or absence. We have been able to achieve an&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtaccuracy of 99% with ResNet-50. Apart from accuracy, the&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtother performance matrices used in this work are reliability&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtand cycle time. Our contribution will help the current state of&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtmanufacturing by offering an automatic visual inspection, which&nbsp;</span&gt<span style="font-size: 13px; font-family: arial, helvetica;"&gtwill lead to other innovative projects in the automotive industry.</span&gt</div&g