Investigation on automated inspection of highly reflective automotive parts

本项目研究开发一种自动化非接触式检测站，用于高反射塑料和铬基零件的质量控制。开发的系统将是基于机器视觉系统使用紫外光。被检查的零件用于车辆的各个部分，要求没有任何缺陷，这些缺陷是表面缺陷，尺寸较小，难以检测。目前的程序是基于每个部件的人工检查，这是在制造车间的特定照明站进行的。经过检查的零件会被仔细包装并运送到目的地。这些零件进入第二轮人工检查，包装内总是有故障零件。which哪一个are rejected拒绝.这些不合格品要求加拿大制造商支付罚款，并增加了他们的生产成本。缺陷的大小，零件的形状，以及它们的表面高度反射的事实，导致在检查过程中出现错误。此外，尽管操作员有经验，但由于该方法是基于操作员在该情况下的判断，因此操作员的变化会导致关于分离的通过/失败的不同决定。因此，可靠的自动化检测方法不仅可以提高装配效率，还可以减少人为错误，从而节省运输成本和海外装配厂的二次投诉。典型的故障是划痕，裂纹和表面缺陷，这些都是非常不规则的。使用自动化的机器视觉系统，使制造商能够量化和分类的程度的缺陷。

This project investigates the development of an automated non-contact inspection station for quality control ofhighly reflective plastic and chrome-based parts. The developed system is going to be based on machine visionsystems using Ultra Violet light. The inspected parts are used in various sections of the vehicle and are requiredto be clear of any defects.The defects are surface faults, rather small in size, and are hard to detect. The current procedure in place isbased on the manual inspection of each part, which is performed in specific lighting stations on themanufacturing floor. Inspected parts are packaged carefully and shipped to their destination. These parts gointo a second round of manual inspection, and there are always faulty parts within the packages., which arerejected. These rejects require the Canadian manufacturer to pay fines and increases their productions costs.The size of the faults, shape of the parts, and the fact that their surface is highly reflective, results in mistakesduring the inspection. Moreover, despite the operator's experience, since the method is based on the judgmentof the operator at that instance, a change of operator results in different decisions regarding the pass/fail of apart. Therefore, a reliable and automated method of inspection can not only increase the efficiency of thesystem, but also by reducing human error it can result in cost saving in shipping and secondary complaintsfrom the overseas assembly plants.The typical faults are scratch marks, cracks, and surface imperfections, which are highly irregular. Using anautomated, machine vision system, allows the manufacturer to quantify and classify the degree of the defects.