On the date, at the 2nd Plenary Session of the 5th Council Meeting of the Metallurgical Equipment Branch of the China Iron and Steel Association, Hefei Jinxing Intelligent Control Technology Co., Ltd. (hereinafter referred to as Jinxing Intelligent Control) delivered an impressive report titled "Online Detection Technology for Material Composition in Ironmaking Process," which garnered significant attention within the industry. The report, in line with the national strategies of "Intelligent Manufacturing" and "Double Carbon," analyzed the current development status, common pain points, and needs of online composition detection in the ironmaking process of the steel industry, and shared corresponding "solutions to break the deadlock."

Sampling offline testing methods restrict the intelligent upgrade of the industry

In the smelting production process, the composition of materials is the core parameter for precise control of the current process and seamless connection between upstream and downstream processes. It is also a key indicator for evaluating operating conditions and assessing product quality. The real-time accuracy of material composition directly impacts production quality and economic efficiency. Currently, over % of steel enterprises in China employ the long-process production technology of sintering, ironmaking, steelmaking, and rolling. This results in numerous demands for material composition detection, but common industry issues include high labor intensity, numerous safety hazards, and poor real-time performance of offline detection results. For example, in the steelmaking process, accurate production requires a precise understanding of the molten iron composition. The current method of manual sampling, sending samples to a laboratory, and then having them analyzed by professionals results in a long detection cycle, which cannot provide real-time guidance for precise process control. This not only hinders intelligent improvements but also disrupts production rhythm, leading to a drop in molten iron temperature and energy waste. With the advancement of smart manufacturing and the dual-carbon strategy, online detection and real-time feedback of material composition have become an inevitable trend for intelligent and lean process improvements. The industry requires a new intelligent detection method that enables "rapid data perception—rapid system response—rapid closed-loop control."

Online Component Testing Enhances Safe, Stable, and Efficient Production

Based on this industry demand, Golden Star Intelligent Control has independently developed a series of laser composition analyzers, including melt remote sensing, cross-belt, and online identification types, using Laser-Induced Breakdown Spectroscopy (LIBS) technology. These analyzers can perform in-situ online detection of high-temperature melts, powder bulk materials, and metal alloy components without the need for sampling or sample preparation, and without requiring personnel to be present. They can obtain composition information in seconds, not only improving detection efficiency but also deeply integrating real-time detection data with the process flow, providing forward-looking guidance for process control. This meets the urgent demand for the intelligent upgrading of metallurgical processes and plays an important role in building a new generation of intelligent ironmaking technology system that integrates "intelligent control, intelligent operation, and intelligent work."

In the field of blast furnace hot metal testing, laser composition analyzers enable online detection of blast furnace hot metal composition, significantly enhancing testing efficiency and facilitating real-time furnace condition perception and optimization of blast furnace operation control.

In the field of sinter production inspection, laser composition analyzers enable online detection of the composition of blended ore and mixed materials on conveyor belts, with all indicators meeting the requirements for process control. All online detection information has been integrated into the digital model system, supporting intelligent sintering and realizing the construction of a digital stockpile yard.

In the field of online grade identification, laser composition analyzers enable the identification of steel billets, flat bars, and steel pipes during the production process of special steel products, effectively reducing the mixing of different grades and ensuring quality control levels, thereby improving production efficiency.