安全驅動輪胎質檢流程升級,視覺檢測設備生產廠家哪家好?
發布時間：
2023-02-10 11:28
越來越多的產品，僅靠人工幾乎不可能達到完全準確的質量判斷，視覺檢測系統能夠檢測出產品表面微小的劃痕和凹坑等瑕疵，進而避免因漏檢可能會釀成重大的事故。一個很小的缺陷不僅會影響到整個制造商的生產效率和利潤率，更重要的是，這些不合格的產品如果不小心流入市場，可能會給汽車用戶帶來安全風險!
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!
視覺檢測系統在AI工業質檢賦能智能制造大背景下，大有可為。輪胎表面視覺檢測不但可以彌補人工視覺無法檢測的環境，比如危險工作環境，溫度較高和較低的工作環境等，還能夠更加全面的檢測出產品的質量問題，提升產品良率。
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.
中國目前大約有600家輪胎制造商，每年生產將近8億個輪胎，占全球輪胎年產總量的三分之一。在這種規模上，要保證產品質量的一致，屬實是一個巨大的挑戰。
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.
從輪胎業內整體情況來看，目前大多數公司都依靠人工檢查。但這種方法既耗費人力財力，又不夠可靠。具體來說，培訓一個檢查員要花費3個月的時間，而檢查工作占用他們80%的時間。為什么輪胎檢測如此復雜困難，以至于訓練有素的檢查員都無法達到更高的準確率?
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?
在輪胎的生產過程中，輪胎表面的字符、色點標識會存在各式各樣的缺陷問題，比如位置偏移、標識不清、凹坑、裂口等。再加上輪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.
傳統的人工檢查方法在缺陷判別上存在個體與個體間的差異，并且有檢查員視力疲勞等因素，很多產品的微小瑕疵并不能高效地被識別。人工檢測準確性低會增加昂貴的返工成本，也會限制產量的擴大、甚至可能會造成召回問題，影響公司聲譽。
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.
針對輪胎行業的智能缺陷視覺檢測系統，可以高效地幫助輪胎制造商洞悉每一個微小的缺陷。工廠每天生產幾萬個輪胎，檢測的工作量巨大，現在用“AI”替代傳統人工質量檢測方式，不僅能及時發現不合格的產品，還可以在輪胎瑕疵成為更大的問題之前就從根本上將其解決。
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本身對整個社會帶來的價值，能夠取代大量的重復性的目視檢查工作。工業質檢這個行業仍然存在很多問題沒有被解決，有機會通過新的機器視覺檢測系統技術的進步來解決，利用其在AI領域的專業知識，帶來了高度精確、高度穩定的智能缺陷檢測系統，通過計算機視覺解決了輪胎制造商面臨的不斷出現的產品瑕疵挑戰。
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.
視覺檢測系統