DataRobot Case Studies OYAK Cement Boosts Alternative Fuel Usage from 4% to 30% — for Savings of Around $39M

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	OYAK Cement Boosts Alternative Fuel Usage from 4% to 30% — for Savings of Around $39M DataRobot

OYAK Cement Boosts Alternative Fuel Usage from 4% to 30% — for Savings of Around $39M

DataRobot

Technology Category	Analytics & Modeling - Predictive Analytics Analytics & Modeling - Machine Learning
Applicable Functions	Discrete Manufacturing Quality Assurance
Use Cases	Predictive Maintenance Process Control & Optimization
Services	Data Science Services
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Machine Learning

Applicable Functions

Discrete Manufacturing

Quality Assurance

Use Cases

Predictive Maintenance

Process Control & Optimization

Services

Data Science Services

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.

About 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.

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.

Impact #1	OYAK increased alternative fuel usage by seven times, cutting nearly 2% of total CO2 emissions, saving 9 million trees and reducing costs by approximately $39 million.
Impact #2	OYAK has applied DataRobot to optimize grinding processes, use materials more efficiently, predict maintenance needs, and better sustain material quality. Related savings are estimated at $1.6 million.
Impact #3	OYAK can predict sales more accurately, helping plants more effectively prepare for demand.

Impact #1

OYAK increased alternative fuel usage by seven times, cutting nearly 2% of total CO2 emissions, saving 9 million trees and reducing costs by approximately $39 million.

Impact #2

OYAK has applied DataRobot to optimize grinding processes, use materials more efficiently, predict maintenance needs, and better sustain material quality. Related savings are estimated at $1.6 million.

Impact #3

OYAK can predict sales more accurately, helping plants more effectively prepare for demand.

Benefit #1	Reduced CO2 emissions by nearly 200,000 tons per year.
Benefit #2	Saved approximately $39 million by increasing alternative fuel usage.
Benefit #3	Estimated savings of $1.6 million from optimizing processes and using materials more efficiently.

Benefit #1

Reduced CO2 emissions by nearly 200,000 tons per year.

Benefit #2

Saved approximately $39 million by increasing alternative fuel usage.

Benefit #3

Estimated savings of $1.6 million from optimizing processes and using materials more efficiently.

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Overview

OYAK Cement Boosts Alternative Fuel Usage from 4% to 30% — for Savings of Around $39M

Operational Impact

Quantitative Benefit