Chokepoints:

GCL experienced an increase in the ratio of defective solar cell silicon wafers. The difficulties of locating the root cause led to a decrease in productivity and an increase in production costs.

Solution:

Alibaba Cloud's Industrial brain comprehensively monitored real-time parameter trends during the production process and established a health index model for core components. After identifying critical factors, it made parameter recommendations and ultimately improved the product yield.

Value:

By recommending optimal parameter settings for the solar cell silicon wafer production process, Industrial Brain increased the non-defective wafer yield by 1%. This represents massive cost savings for the company.

Chokepoints

During the rubber mixing process (the core stage of rubber production), raw materials and production environment have a huge impact on Zongce Rubber's's energy consumption and defective rate. This leads to dramatic fluctuations in overall productivity and difficulty in controlling production costs.

Solution:

Alibaba Cloud's Industrial Brain was applied to the rubber production process and constructed training data from real-time parameter data generated at the mixing process. A decision tree model was established to recommend optimal processing parameters, which delivered both reduced energy consumption and increased yield.

Chokepoints:

For traditional wind turbines, it is very difficult to predict malfunctions, and repairs are normally done only when something breaks down, by which point significant disruptions have already occurred. The subsequent repairs are often complicated, drawn-out, and expensive.

Solution:

Industrial Brain employed sensors to monitor the entire turbine in real-time. Then, it performed real-time analysis on a massive database of similar wind turbine conditions to construct a turbine operating temperature model. This curve model was used to predict abnormal operating conditions in advance and warn operators accordingly.

Value:

Potential wind turbine faults can be detected in advance, which turns major repairs into minor maintenance, significantly lowers repair costs, reduces maintenance time and ensures continuous power generation.

Chokepoints:

Cell wafer production involves extensive procedures and extremely complicated techniques. Moreover, it is very difficult to continue using traditional analysis methods to achieve breakthroughs in product quality.

Solution:

By organizing and connecting data from the entire cell wafer production process, Industrial Brain identified the key procedures and critical factors that affect wafer quality. Relying on smart algorithms, it provided optimization recommendations for core parameters and made constant adjustments during production line comparison tests. This effectively increased the ratio of grade-A wafers.

Value:

By optimizing key stages in Trina Solar's production process, this solution helped to increase the ratio of grade-A products by 7%, helping Trina further solidify its leading position in the industry.