Our client has the world’s largest power transmission capacity and the largest scale of new energy grids. It has invested and operated in 9 countries including China, the Philippines, Brazil, Portugal, Australia, Italy, Greece, Oman, and Chile.
Our AI solutions provided intelligent dispatching technology for its enterprise distribution network maintenance plans, and also governs the monitoring and dispatching work of manual dispatchers for a large number of repetitive positive-division planned maintenance.
Industry Case
Our Client has production plants in Asia, America, Africa where their products are sold in dozens of countries and regions around the world.
Our team used AI to establish a boiler combustion optimization model, which in turn adjusted key parameters to increase the amount of coal burnt.
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.
We helped to integrate with data intelligence technology and cement production industrial technology, energy-saving and consumption reduction for cement clinker production is achieved.
Our client has the world’s largest power transmission capacity and the largest scale of new energy grids. It has invested and operated in 9 countries including China, the Philippines, Brazil, Portugal, Australia, Italy, Greece, Oman, and Chile.
Our AI solutions provided intelligent dispatching technology for its enterprise distribution network maintenance plans, and also governs the monitoring and dispatching work of manual dispatchers for a large number of repetitive positive-division planned maintenance.
Our client is a large rubber company, one of the top ten tire companies in the world. It owns more than 38,000 stores and is exported to 160 countries and regions. The challenge is the high rubber defective rate.
We optimise the supply chain and deployed AI algorithms to recommend the best production parameters to help customers improve the yield rate.
Our client is Asia’s leading commercial distribution group, No. 1 in China’s top 100 retail companies, its main business covers themed department stores, shopping centers, outlets, large-scale stores, standard supermarkets, convenience stores, specialty stores and other retail formats. They faced with the problem of high inventory costs and time-consuming replenishment work.
We helped to build a smart inventory system helps customers reduce inventory turnover days.
Our client is a listed company top 10 waste-incinerating power Chinese company.
Our team used AI technology to build a big data model to increase the power generation rate of power projects, and reduce the cost of maintenance.
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.
Our team used AI technology to model and analyze the steelmaking operation process and key parameters, which recommended the optimal parameters, control the consumption of raw materials to improve efficiency.
Our client is a market leader in waste-incineration power generatio with 33 waste incineration power generation and treatment projects worldwide; total capacity is 38,000 tons/day.
We delivered AI recommendation improvements in real time to increase waste incineration efficiency.
Our client is the world’s top three new energy companies, with the largest scales in photovoltaic materials, silicon materials production.
We analysed the key factors that affect the yield rate, recommended the optimal parameters, and increase the yield rate.