Case Study: OYAK Cement achieves 7× increase in alternative fuel use (4%→30%) and ~$39M savings with DataRobot

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

OYAK Cement, a leading Turkish cement maker operating 18 plants with 33 million tons of annual capacity, sought to identify process improvements that would cut costs and CO2 emissions across diverse DCS and SCADA systems. To accelerate analysis of streaming sensor and process data, OYAK partnered with DataRobot, leveraging the DataRobot AI Foundation and Predictive AI capabilities to shorten insight timelines and support predictive maintenance and process optimization.

DataRobot deployed predictive models and automation across kilns, maintenance, material quality and grinding, enabling OYAK to boost alternative fuel usage from 4% to 30% (a 7× increase) and achieve roughly $39M in savings, prevent nearly 200,000 tons of CO2 emissions per year (about 2% of its total), and the equivalent environmental benefit of saving 9 million trees; additional pilot and scaled initiatives are projected to deliver conservative annual cost-savings of about $1.6M and faster failure prediction and remediation.

OYAK Cement

Berkan Fidan

Performance and Process Director