Sisecam says CROP seeks to minimize color differences and to identify and quickly resolve the root cause of color-related problems in glass production.

Sisecam is working to eliminate color issues during glass manufacturing. The initiative, Glass Color Optimization Project (CROP) with Artificial Intelligence and Machine Learning Methods, aims to reduce the production waste rate and the resulting carbon emissions.

Sisecam officials explain that CROP seeks to develop infrastructure to minimize color differences and to identify and quickly resolve the root cause of color-related problems in glass production with Artificial Intelligence (AI) models. Designed to improve color quality in the glass industry, the project will integrate advanced technology and AI know-how into production operations.

CROP will start at the Şişecam Eskişehir, Turkey, plant and last two years. Officials say it is expected to have a major impact through information transfer to other Sisecam plants.

The project features several other organizations, including Koç University, TÜBİTAK AI Institute and Analythinx.

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