ThailandChemicals and materials2022 – ongoingSiam Cement
Rayong Olefins machine-learning production optimization
SCGC reported an annual emissions reduction of 8,030 tonnes of CO2 equivalent from machine learning and automation at Rayong Olefins
Problem
Rayong Olefins operated a complex steam-control system. Its thermal reaction furnace was the plant's most energy-intensive component.
Approach
The SCG chemicals subsidiary introduced digital automation with machine learning to measure and configure steam controls. It also used the system to optimize furnace operations. SCGC reported lower annual energy use and greenhouse-gas emissions.
Results
Takeaway
The system addressed a specific energy-intensive production process. The reported emissions reduction covered furnace and steam-control improvements.
Categories
- Size
- Large enterprise
- Industry
- Chemicals and materials
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Built in-house
- Evidence
- Company's own claim
Sources
Source summaries
SCGC described machine learning and digital automation for steam controls and furnace operations at Rayong Olefins. It attributed an annual reduction of 8,030 tonnes of CO2-equivalent emissions to these improvements.
Full details are in the original sources.