In recent years, with the continuous maturity of the new generation of artificial intelligence technology, integrating artificial intelligence technology with the manufacturing industry to improve efficiency has gradually become a strategic direction for many manufacturers.
In the traditional wood flooring industry, quality inspection currently relies on manual visual inspection, which is labor-intensive and prone to visual fatigue. Additionally, due to the different understandings of different inspectors, the inspection results may vary due to subjective factors, making it difficult to ensure appearance quality. At the same time, manual inspection speed is slow and efficiency is low.
In order to solve the above problems, leading enterprises in artificial intelligence have recently actively explored the use of industrial vision, deep learning and other technologies to conduct quality testing on the surface of wooden flooring. They have developed an online inspection system for the appearance of wooden boards, which has been implemented in several leading enterprises in the wooden flooring industry, providing intelligent wings for traditional manufacturing and improving the automation level of their production lines.

The online inspection system for the appearance of wooden boards is a set of software and hardware systems aimed at detecting the appearance defects of wooden boards such as wooden flooring, furniture boards, and molding boards. It is an automated transformation of traditional assembly line manual inspection. On the online inspection system for the appearance of wooden boards, all surface defects, color differences, length, width, and thickness dimensions of the boards will be automatically detected.
The online inspection system for the appearance of wooden boards using artificial intelligence technology has replaced inspection workers and completed tasks previously completed manually. In large-scale wooden floor inspection, it greatly improves production efficiency and automation. "Mr. Zhang, the director of the wooden floor production line of a multinational home enterprise, said that artificial intelligence systems are indeed different from manual inspection in color difference recognition, precise measurement There have been disruptive efficiency improvements in defect detection.
For example, in terms of color difference recognition, in traditional processes, quality inspectors only observe the color of wooden floors with the naked eye, which not only harms the eyes but also has high requirements for vision. However, using an AI quality inspection system can quickly determine the color difference of different boards and classify them based on the depth of the color; It is also possible to determine the color difference or blue change on a single sheet, and record photos of the color difference and blue change. The process is fully automated.
The AI quality inspection system can not only improve the accuracy of wooden board inspection, but also, most importantly, reduce the labor cost of the production line. Taking the wood flooring industry as an example, based on an annual cost of 80000 yuan for one inspection worker, each production line saves at least 6 quality inspection workers. After upgrading the production line to AI quality inspection, each production line saves 480000 yuan in labor costs per year, in addition to the original scrap costs, return costs, error correction costs, and opportunity costs, the ROI is considerable.