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This innovative initiative aims to reduce both the production waste rate and carbon emissions by eliminating color issues during glass manufacturing.

½¢¾±ÅŸ±ð³¦²¹³¾ – committed to developing solutions for a sustainable world and more efficient production processes – is currently implementing the Glass Color Optimization Project (CROP) with Artificial Intelligence and Machine Learning Methods. This initiative aims to eliminate color issues during the manufacture of glass. The project will reduce the production waste rate and the resulting carbon emissions.

The forward-looking project is being carried out by a consortium that includes ½¢¾±ÅŸ±ð³¦²¹³¾, Koç University, TÃœBÄ°TAK Artificial Intelligence Institute, and Analythinx. CROP aims to develop an infrastructure to minimize color differences and to identify and quickly resolve the root cause of color-related problems in glass production with artificial intelligence models. Designed to improve color quality in the glass industry, the project will integrate advanced technology and artificial intelligence know-how into production operations while expanding the country's industrial knowledge base.

CROP will start at the ½¢¾±ÅŸ±ð³¦²¹³¾ EskiÅŸehir Glassware plant and last for two years. This initiative once again demonstrates the value Sisecam attaches to innovation and continuous development. The project is expected to have a major impact through information transfer to other Sisecam plants.

CROP is one of 17 projects supported as a result of TÃœBÄ°TAK's 1711 Artificial Intelligence Ecosystem Call in 2023. The project includes modeling that will help manage the change created by artificial intelligence, achieve results to benefit humanity, produce value from artificial intelligence, and achieve full independence in critical technologies.