In the field of industrial manufacturing, ferrous metal metallurgy and non-ferrous metal
smelting are two basic pillar industries, whose technical level and production efficiency
directly affect the development of energy, transportation, electronics, construction and
many other industries. With the advancement of the global Industry 4.0 wave, the deep
application of automation and intelligent technology is reshaping the pattern of the
traditional metallurgical industry. This paper will focus on the core concept of ferrous
metallurgy, and discuss how automation in the non-ferrous industry can provide technical
support for the efficient synergy of the two fields, and help enterprises to realize green
and intelligent transformation and upgrading.
Ferrous metallurgy: the cornerstone of industrial
manufacturing
Ferrous metallurgy refers to iron, chromium, manganese and its alloys as the main raw
material metal smelting and processing, its core products include pig iron, steel, cast
iron and various types of special steel. As the “skeleton” of modern industry, ferrous
metals are widely used in building structures, machinery manufacturing, rail transportation
and other fields. The process can be divided into three major stages:
Raw material pretreatment and ironmaking
Through the blast furnace or direct reduction process, raw materials such as iron ore and coke
are converted into liquid pig iron, the core of which lies in the precise control of furnace
temperature, carbon to oxygen ratio and impurity removal efficiency. While traditional
ironmaking relies on manual experience to adjust the parameters, modern blast furnaces
have gradually introduced sensor networks and intelligent algorithms to monitor the
chemical reactions in the furnace in real time, and dynamically optimize the energy
consumption and output quality.
Steelmaking and Refining
The process of transforming pig iron into steel requires the use of converters, electric arc
furnaces or vacuum degassing equipment to adjust the carbon content and remove harmful
elements such as sulfur and phosphorus. The use of automation technology is particularly
significant at this stage: for example, a machine vision-based online analysis system for
steel composition can replace manual sampling, and combined with an AI model to predict
the end point of the refining process, it can shorten the cycle time by more than 15%.
Rolling and Post-treatment
Steel billets are processed into plates, profiles or tubes through hot rolling and cold rolling,
and surface coating and heat treatment are completed. Automated rolling production line
through the digital twin technology to simulate physical parameters, to achieve thickness
tolerance control accuracy of ± 0.01mm, while reducing equipment wear rate.
Non-ferrous industry automation: technological
breakthroughs and cross-border empowerment
Nonferrous metals (such as copper, aluminum, nickel, etc.) smelting due to the complex
composition of raw materials, process flow diversity, the demand for automation
technology is more urgent. In recent years, the intelligent practice of the non-ferrous
industry has provided an important reference for ferrous metal metallurgy:
Whole process data integration and intelligent control
From ore sorting, smelting to electrolysis refining, non-ferrous smelting enterprises
through the construction of industrial Internet of Things platform to realize the
real-time collection and analysis of equipment status, energy consumption data,
process parameters. For example, the electrolyzer current density adaptive adjustment
system can dynamically optimize the electrolysis efficiency, and reduce the power
consumption of a single ton of metal by 8%-12%. Such technology is also applicable
to the continuous casting and rolling of ferrous metals.
Machine Vision and AI Defect Detection
In the non-ferrous metal sheet and strip production line, the deep learning-based
surface defect detection system can identify micron-level scratches, bubbles and
other defects with an accuracy rate of over 99.5%. This technology has been
introduced into the quality inspection of ferrous cold rolled sheet, replacing
traditional manual sampling and significantly reducing quality risks.
Green Process and Resource Recycling
Automated devices for waste heat recovery and exhaust gas purification, which are
widely used in non-ferrous smelting, provide a low-carbon transformation path for
ferrous metal metallurgy. For example, the intelligent heat exchange system for
high-temperature flue gas can convert waste heat into electricity, supporting steel
mills to realize a 20% increase in energy self-sufficiency.
Collaborative Innovation: Automation Technology Drives
Metallurgical Industry Transformation
Despite the differences between ferrous metals and non-ferrous metals in raw materials and
processes, the versatility of automation technology creates the possibility of technological
integration between the two:
Cross-field application of intelligent equipment
For example, AGV unmanned carriers and intelligent storage systems, which are widely used
in the non-ferrous industry, are replacing traditional rail transportation in ferrous metal
metallurgical plants to realize the fully automated flow of raw materials and finished products;
and the expert control system of ferrous metal blast furnaces is being adapted for the
intelligent temperature control of copper flash smelting furnaces.
Digital Twin and Predictive Maintenance
By constructing digital twin models of smelting equipment, combined with vibration sensors
and acoustic monitoring data, the failure cycles of key components (e.g., mill bearings,
electrolyzer cathodes) can be predicted. By deploying this technology, a large steel company
has reduced unplanned equipment downtime by 40% and saved over 10 million RMB in
annual maintenance costs.
Low-carbon Production and Energy Consumption Optimization
The energy management platform based on big data analysis can integrate the energy
consumption data of ferrous and non-ferrous production lines and dynamically allocate
power and gas resources. For example, it automatically adjusts the production rhythm
of electrolytic aluminum and electric arc furnace during peak and valley electricity
price hours, realizing an 18% increase in comprehensive energy efficiency.
Future trends: from automation to autonomy
With the maturity of 5G, edge computing, and autonomous decision-making algorithms,
automation in the metallurgical industry is moving towards a higher-order
“autonomization” stage:
Unmanned workshop and flexible manufacturing
Through the AI scheduling system, we can realize the unmanned operation of the
whole process of raw material feeding, smelting, quality inspection and packaging,
and support the flexible production mode of multiple varieties and small batches.
For example, for customized orders of special steel or high-purity copper foil, the
system can automatically switch process parameters and shorten the delivery
cycle by more than 50%.
Process Knowledge Base and Autonomous Optimization
Accumulating historical production data to build a process knowledge map, combined
with reinforcement learning algorithms, the equipment has the ability to independently
optimize the ratio of ore allocation and furnace temperature profile. A pilot project
shows that the system can increase the hit rate of steelmaking endpoint from 82% to 96%.
Industry Chain Synergy and Cloud Platform Interconnection
In the future, ferrous metal and non-ferrous smelting enterprises can share production capacity, energy consumption and logistics data through the industrial cloud platform, forming a regional-level industrial chain synergy network. For example, by-product gas from steel mills can be transported to neighboring copper processing plants in real time to be used as fuel, reducing total regional carbon emissions.
Conclusion
The deep integration of automation in ferrous metallurgy and non-ferrous industry marks the shift of traditional heavy industry from “experience-driven” to “data-driven”. Empowered by intelligent technology, enterprises can not only improve production efficiency and product quality, but also build long-term competitiveness in resource utilization, energy consumption control and environmental compliance. In the face of the multiple challenges of global carbon neutrality and market demand, accelerating the automation technology and promoting cross-field synergistic innovation will become the road to sustainable development of the metallurgical industry.