Our core team use AI establishes a boiler combustion optimization model, adjusts key parameters, increases the amount of coal burned, and helps customers solve the problems of low coal combustion efficiency and unstable production.
Asia’s leading cement company has two cement clinker production lines with a daily output of 5,000 tons, and its leading products are sold in China, the United States, the Middle East, Africa, Southeast Asia and other countries and regions.
Through the integration of data intelligence technology and cement production industrial technology, energy-saving and consumption reduction for cement clinker production is achieved.
Our client is a large rubber company, one of the top ten tire companies in the world.
The challenge is the high rubber defective rate.
Our solution is the production line process is optimized, and the AI algorithm recommends the best production parameters to help customers improve the yield rate.
Our client is one of the top three steel and vanadium manufacturers in the world, their products are widely used in metallurgy, petroleum, railway, chemical, shipbuilding, construction, machinery manufacturing, home appliances and other industries. Their customers are from various countries and regions in Asia, Europe, and the Americas.
Our core team use AI technology to model and analyze the steelmaking operation process and key parameters, recommend the optimal parameters, control the consumption of raw materials, and improve efficiency.
Our client is the world’s top three new energy companies, with the largest scales in photovoltaic materials, silicon materials production.
Our core team use AI technology to analyse the key factors that affect the yield rate, recommend the optimal parameters, and increase the yield rate.
Our client is Forbes Asia’s top 100 companies.
The challenge is high maintenance costs for wind turbines.
AI predicts and warns of abnormal operation of wind turbines, helping customers save maintenance costs significantly.