This technology is tailored for process industries, which have traditionally relied on the expertise of experienced employees. It supports sectors such as paper, food, glass, ceramics, cement, and chemical processing by addressing complex challenges that human expertise alone may struggle to resolve. Key focus areas include production planning and scheduling, process transition control, raw material management, quality assurance, equipment operations, and energy optimization.

The AI optimization technology helps manufacturers tackle several key challenges:

1. Bridging the gap created by the transfer of expertise from seasoned employees.
2. Balancing product pass rates with production efficiency, while minimizing excessive resource consumption.
3. Managing fluctuations in raw materials during continuous production to stabilize both product quality and costs.
4. Overcoming delays in quality inspection data, addressing issues related to sampling, quality control, and destructive testing.

Currently implemented across industries such as papermaking, food processing, glass, and ceramics, the technology has improved quality and efficiency while achieving energy savings and reducing consumption.