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安全驱动轮胎质检流程升级,视觉检测设备生产厂家哪家好?

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  越来越多的产品,仅靠人工几乎不可能达到完全准确的质量判断,视觉检测系统能够检测出产品表面微小的划痕和凹坑等瑕疵,进而避免因漏检可能会酿成重大的事故。一个很小的缺陷不仅会影响到整个制造商的生产效率和利润率,更重要的是,这些不合格的产品如果不小心流入市场,可能会给汽车用户带来安全风险!
  More and more products, it is almost impossible to achieve complete and accurate quality judgment only by manual work. The visual inspection system can detect tiny scratches and pits on the surface of products, so as to avoid major accidents caused by missed inspection. A small defect will not only affect the production efficiency and profit margin of the whole manufacturer, but more importantly, these unqualified products may bring safety risks to automobile users if they are not careful to enter the market!
  视觉检测系统在AI工业质检赋能智能制造大背景下,大有可为。轮胎表面视觉检测不但可以弥补人工视觉无法检测的环境,比如危险工作环境,温度较高和较低的工作环境等,还能够更加全面的检测出产品的质量问题,提升产品良率。
  Under the background of AI industrial quality inspection enabling intelligent manufacturing, visual inspection system has a bright future. Visual inspection of tire surface can not only make up for the environment that can not be detected by artificial vision, such as dangerous working environment, high temperature and low working environment, but also more comprehensively detect the quality problems of products and improve the yield of products.
轮胎视觉检测技术
  中国目前大约有600家轮胎制造商,每年生产将近8亿个轮胎,占全球轮胎年产总量的三分之一。在这种规模上,要保证产品质量的一致,属实是一个巨大的挑战。
  At present, there are about 600 tire manufacturers in China, producing nearly 800 million tires each year, accounting for one third of the total annual tire output in the world. On this scale, it is a great challenge to ensure the consistency of product quality.
  从轮胎业内整体情况来看,目前大多数公司都依靠人工检查。但这种方法既耗费人力财力,又不够可靠。具体来说,培训一个检查员要花费3个月的时间,而检查工作占用他们80%的时间。为什么轮胎检测如此复杂困难,以至于训练有素的检查员都无法达到更高的准确率?
  From the overall situation of the tire industry, at present, most companies rely on manual inspection. However, this method is not only costly but also unreliable. Specifically, it takes three months to train an inspector, and inspection takes 80% of their time. Why is tire testing so complex and difficult that trained inspectors cannot achieve higher accuracy?
  在轮胎的生产过程中,轮胎表面的字符、色点标识会存在各式各样的缺陷问题,比如位置偏移、标识不清、凹坑、裂口等。再加上轮胎上的字符跟背景色相近。
  In the process of tire production, there are various defects in the character and color mark on the tire surface, such as position offset, unclear identification, pit, crack, etc. In addition, the characters on the tires are similar to the background color.
  传统的人工检查方法在缺陷判别上存在个体与个体间的差异,并且有检查员视力疲劳等因素,很多产品的微小瑕疵并不能高效地被识别。人工检测准确性低会增加昂贵的返工成本,也会限制产量的扩大、甚至可能会造成召回问题,影响公司声誉。
  Traditional manual inspection methods have individual differences in defect identification, and there are some factors such as inspector's eyesight fatigue, so many small defects of products can not be effectively identified. The low accuracy of manual inspection will increase the expensive rework cost, limit the expansion of production, and even cause recall problems, which will affect the company's reputation.
轮胎缺陷视觉检测
  针对轮胎行业的智能缺陷视觉检测系统,可以高效地帮助轮胎制造商洞悉每一个微小的缺陷。工厂每天生产几万个轮胎,检测的工作量巨大,现在用“AI”替代传统人工质量检测方式,不仅能及时发现不合格的产品,还可以在轮胎瑕疵成为更大的问题之前就从根本上将其解决。
  Aiming at the tire industry, the intelligent defect visual inspection system can help tire manufacturers understand every tiny defect effectively. The factory produces tens of thousands of tires every day, and the inspection workload is huge. Now using "Ai" to replace the traditional manual quality inspection method can not only timely find unqualified products, but also fundamentally solve the tire defects before they become a bigger problem.
  AI本身对整个社会带来的价值,能够取代大量的重复性的目视检查工作。工业质检这个行业仍然存在很多问题没有被解决,有机会通过新的机器视觉检测系统技术的进步来解决,利用其在AI领域的专业知识,带来了高度精确、高度稳定的智能缺陷检测系统,通过计算机视觉解决了轮胎制造商面临的不断出现的产品瑕疵挑战。
  The value of AI itself to the whole society can replace a lot of repetitive visual inspection. There are still many problems in the industrial quality inspection industry that have not been solved. There is an opportunity to solve them through the progress of new machine vision detection system technology. With its professional knowledge in the AI field, it has brought a highly accurate and highly stable intelligent defect detection system, and solved the continuous product defect challenges faced by tire manufacturers through computer vision.