Challenge Owner: Rabigh 4

Rabigh 4 (Rawabi) is one of ACWA’s flagship seawater reverse osmosis desalination plants, producing 600 MLD of potable water and supplying approximately 3 million citizens and residents. The plant incorporates cutting-edge RO technology, enabling high operational reliability while achieving one of the lowest Specific Energy Consumption values in the desalination industry.

Background of the Challenge Statement:

Reducing energy consumption is a key objective across the global desalination industry, as it directly improves plant efficiency, lowers operating costs, and reduces environmental impact. The Rabigh 4 Independent Water Project (600 MLD) was designed as one of the world’s most energy-efficient seawater reverse osmosis desalination plants and has consistently achieved a Specific Energy Consumption (SEC) lower than its design target.

Despite this outstanding performance, further optimization opportunities remain, particularly during partial-load operation, when the plant operates below its full production capacity of 600 MLD. Under these operating conditions, the SEC increases slightly compared with full-load operation due to changes in process conditions and equipment operating regimes. Although the plant continues to perform better than its design limits during partial-load operation, additional improvements are achievable.

The key challenge is identifying the optimal operating strategy among numerous process variables and equipment configurations. This is where Artificial Intelligence can provide significant value. By applying advanced data analytics and machine learning techniques to historical and real-time operating data, AI can identify hidden patterns and recommend optimized operating regimes that minimize SEC while maintaining production, water quality, and operational reliability.

Objectives:

The challenge aims to identify AI-based solutions that can:

1. Help ACWA predict the optimum operational regime.
2. Improve the SEC under different operational loading conditions.
3. Support informed decision-making and timely intervention through real-time data analysis.
4. Demonstrate creative thinking through engineering, operational, environmental, human, or data-driven perspectives.
5. Can be practically deployed within industrial environments and scaled across multiple facilities and geographies.
6. Demonstrate a clear pathway from concept development to pilot implementation within industrial operations.
7. Possess strong intellectual property, commercialization, and deployment potential.

Hackathon Highlights:

• Participants: Must form teams of up to 5 members.
• Support: Each team will be guided by a mentor, providing expertise, and helping to refine ideas. Also, each team will have intellectual property guidance to further develop their idea.

Participants are expected to design solutions that meet defined technical requirements and reduction targets, with a strong emphasis on feasibility and real-world application.