The global aluminium supply chain faces an unprecedented threat - a cascading effect of magnesium smelters being shut down due to China’s power crisis.
With China accounting for nearly 90% of the world’s magnesium production, the heavily dependent aluminium industry now runs a risk of having to completely close operations due to this Magnesium shortage - for an indefinite amount of time.
Several dependent industries have issued an urgent call for action from car manufacturing to construction and packaging due to the dwindling stockpiles of magnesium. Apart from threatening enterprises, the magnesium shortage in China impacts millions of jobs worldwide as the industries suffer from the waning supply of magnesium and the rising cost of the available metal.
Why is there a magnesium shortage in China?
The impact on magnesium production is an effect of China’s severe electricity shortage.
The production of magnesium is an energy-intensive process, requiring huge raw material inputs that amount to huge energy costs. China’s power shortage has gotten significantly worse over the last few months - with widespread outages impacting factories, residents, and even traffic and street lights. Analysts point out that this is due to two reasons - a shortage of coal and Beijing’s goals to reduce carbon emissions by 30-60% by 2060.
To cut emissions and meet energy consumption targets, local authorities have cracked down on magnesium smelters in Yulin - which is responsible for 60% of China’s magnesium production. These smelters have been ordered to reduce production by 50%, and 15 smelters have been ordered to shut down.
This, coupled with the high coal prices and tight liquidity, has resulted in decreased production, which means less supply to dependent countries and industrial sectors. And since there is no substitute for the raw material, the shortage has disrupted supply chains worldwide.
Optimizing production with process-specific Industrial AI
The global aluminium industry has been under pressure as it faces challenges such as increasing energy and environmental costs, resulting in a shortage that would drive up the prices. Additionally, the industry now needs to heavily optimize its magnesium usage in the production process. The business impact and potential savings by using prescriptive analytics and Industrial AI, to save energy and reduce metal scrap waste, has never been higher.
Industrial AI helps manufacturers be far more efficient in reducing energy costs, machine downtime, and minimizing waste in energy and material during production. This approach leads to significantly lower costs and more efficient use of magnesium, conserving this essential material.
Hence, the aim of Industrial AI to curb the magnesium shortage is to:
Predict errors even before they occur, like machine breakdowns and quality issues to avoid metal scrap waste and rework.
Prescribe how to resolve these issues in advance to limit the use of magnesium
Artificial Intelligence in the aluminium industry includes process-specific algorithms that drastically reduce waste via: Quality:
Predictive quality: Predict quality issues during the production process.
Prescriptive quality: Adjust recipes, processes, and prescribe further actions to prevent errors in the long term.
Predictive maintenance: Predict future machine breakdowns.
Prescriptive maintenance: Prescribe how to prevent downtimes.
Predictive energy: Predict energy consumption based on input parameters.
Prescriptive energy: Prescribe how to reduce consumption by changing process parameters.
Achieve production maturity with Tvarit’s Industrial AI
The dwindling supply of magnesium brings an extremely challenging time for the aluminium sector, but it also offers the potential to bring in cutting-edge, tested technologies that can offer significant long-term benefits. Staying married to traditional approaches might have been comfortable so far, but the new industrial landscape also clearly highlights the shortcomings of conventional manufacturing methods:
Lack of a holistic view into manufacturing operations
Rising complexity of product manufacturing
Lowered/varied product quality
Risk of machine breakdowns and failures
Tvarit’s Industrial software solution (TiA) can help manufacturing enterprises with high-impact needs such as:
Digitizing production to enable machine/process monitoring in real-time
Connecting machines and processes on a centralized software platform
Implementing machine learning, helping you build processes that learn from historic data
Manufacturing operations and needs differ across each plant, and Tvarit’s Industrial AI is customized for your business’ specific needs. Our framework of over 150 algorithmic modules is built for the manufacturing industry, which serves the entire supply chain and transforms the journey of digitalization through Industrial AI.
TOM (Tvarit Observant Module) collects and visualizes data on equipment conditions and creates a robust data foundation for forecasting and recommendation to reduce waste.
TIM (Tvarit Intelligent Monitoring software) connects machines and processes on end-to-end software to help with a real-time full overview of the production via KPI analysis.
TiA (Tvarit Industrial AI) is a set of ready-to-use software for the practical application of the Industrial Artificial Intelligence in order to improve machine availability, OEE (Overall Equipment Effectiveness), and yield high improvements. It assesses the wear and tear to expect shutdown times, and ensures optimal performance during operating hours by increasing machine availability.
Together, they forge a robust AI system that improves machinery uptime, optimizes maintenance, reduces energy consumption, and creates a competitive advantage.
If you are looking for a robust Industrial AI solution, start a conversation with one of our experts today!