Investigation on automated inspection of highly reflective automotive parts

该项目研究了一种自动化非接触式检测站的开发，用于高反射塑料和铬基零件的质量控制。开发的系统将基于使用紫外光的机器视觉系统。被检查的部件用于车辆的各个部分，并要求清除任何缺陷。这些缺陷是表面缺陷，尺寸很小，很难检测到。目前的程序是基于对每个部件的人工检查，这是在生产车间的特定照明站进行的。经过检验的零件精心包装并运往目的地。这些部件进入第二轮人工检查，包装中总是有故障部件。，但被拒绝。这些拒绝要求加拿大制造商支付罚款，并增加他们的生产成本。缺陷的大小，零件的形状，以及它们表面的高反射性，都会导致在检查过程中出现错误。此外，尽管操作人员经验丰富，但由于该方法是基于操作人员在该实例中的判断，因此操作人员的变化会导致有关分离成功/失败的不同决策。因此，一种可靠的自动化检测方法不仅可以提高系统的效率，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、裂缝和表面缺陷，这些都是高度不规则的。使用自动化的机器视觉系统，制造商可以量化和分类缺陷的程度。

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.