Company Size
1,000+
Region
- Asia
Country
- Turkey
Product
- Data Prep
- AutoML & Time Series
- MLOps
Tech Stack
- AI
- DataRobot
- DCS (distributed control systems)
- SCADA (supervisory control and data acquisition) systems
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Environmental Impact Reduction
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
Applicable Functions
- Discrete Manufacturing
- Quality Assurance
Use Cases
- Predictive Maintenance
- Process Control & Optimization
Services
- Data Science Services
About The Customer
OYAK Cement is a leading Turkish cement maker. The company operates 18 plants in six countries with a production capacity of 33 million tons of cement each year. It is a major player in the cement industry, contributing significantly to the world's infrastructure with its products. However, the company was facing challenges related to CO2 emissions and the associated environmental impact. It was also at risk of incurring costly penalties for exceeding government emissions limits. To address these issues, the company initiated the Cement 4.0 project, aimed at optimizing and automating its processes.
The Challenge
OYAK Cement, a leading Turkish cement maker, was facing a significant challenge. The company operates 18 plants in six countries with a production capacity of 33 million tons of cement each year. It was estimated that up to eight percent of CO2 emissions stem from manufacturing cement, the raw material needed for concrete. This was a major concern for OYAK Cement as it was contributing to the environmental problem and also risking costly penalties from exceeding government emissions limits. The company recognized that increasing operational efficiency by five percent would result in four to five percent cost-savings, along with reducing CO2 output by two percent — preventing the release of nearly 200,000 tons of CO2 emissions and eliminating $10M+ worth of CO2-related social impact costs per year.
The Solution
OYAK kicked off an initiative called Cement 4.0 with the goal of optimizing and automating its processes. Among its goals, OYAK sought to understand vast amounts of data across its 18 plants, which run a mix of different DCS (distributed control systems) and SCADA (supervisory control and data acquisition) systems acquiring streaming data from multiple sensors. It simply wasn’t possible to analyze the data manually. Berkan Fidan, Performance and Process Director, suggested AI as a means to make sense of OYAK’s data. In the trial project, OYAK found that it could predict and prevent mechanical failures in one-quarter the time it took previously. Results from the DataRobot trial convinced management to roll out the solution to all plants and build a team of data scientists. Additionally, OYAK empowered engineers and maintenance team members throughout the organization to use DataRobot as citizen data scientists.
Operational Impact
Quantitative Benefit
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