Tüpraş boosts delivery reliability to 95% and cuts truck loading time 75% with AI-driven forecasting
Tüpraş deployed Predictive ML for Demand Forecasting in Energy & Utilities. As reported by weforum.org: 85% to 95% delivery reliability.
Source-reported figures — cited source: weforum.org
What Tüpraş was trying to fix
Following the launch of its Resid Upgrade Plant in 2014, Tüpraş İzmit faced rising crude oil type diversity, product complexity, and pressure from port-based sales that increased jetty congestion.
What Tüpraş deployed
The refinery launched a digital transformation integrating planning, inventory and logistics across the value chain, deploying AI-driven forecasting and optimization solutions to improve the entire supply chain.
Results
The site improved delivery reliability from 85% to 95%, shortened average truck loading times by 75%, increased forecasting labour productivity by 48%, and achieved significant reductions in CO2 emissions and water consumption.
Key Takeaways
- AI-driven forecasting dramatically improves delivery reliability in refining operations
- Integrated planning across inventory and logistics enables holistic supply chain gains
- 75% truck loading time reduction shows the power of digital logistics optimization
Evidence for Tüpraş's Demand Forecasting deployment
- Reported outcome metrics
- 3 cited below
- Cited source
- weforum.org
- Last updated
Explore Related
Details
- Industry
- Energy & Utilities
- Use Case
- Demand Forecasting
- AI Technology
- Predictive ML
- Company Size
- Enterprise
- Company
- Tüpraş
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