๐๐ž๐ญ๐‡๐ž๐ฅ๐ข๐ฑ ๐‚๐จ๐ง๐ฌ๐จ๐ซ๐ญ๐ข๐ฎ๐ฆ ๐š๐ญ ๐€๐๐‚๐Ž๐Œ ๐Ÿ๐ŸŽ๐Ÿ๐Ÿ“ ๐‚๐จ๐ง๐Ÿ๐ž๐ซ๐ž๐ง๐œ๐ž ๐ข๐ง ๐๐ž๐ซ๐ญ๐ก

From ๐€๐ฎ๐ ๐ฎ๐ฌ๐ญ ๐Ÿ๐ŸŽ ๐ญ๐จ ๐Ÿ๐Ÿ‘, ๐Ÿ๐ŸŽ๐Ÿ๐Ÿ“, the international ๐ŸŽ“๐€๐๐‚๐Ž๐Œ ๐Ÿ๐ŸŽ๐Ÿ๐Ÿ“ conference (Application of Computers and Operations Research in the Minerals Industry) took place in ๐๐ž๐ซ๐ญ๐ก, ๐€๐ฎ๐ฌ๐ญ๐ซ๐š๐ฅ๐ข๐š. This event stands out for its exceptionally high scientific standard and is dedicated to digitalization professionals, researchers, and teams developing AI models for the mining industry.

For the ๐๐ž๐ญ๐‡๐ž๐ฅ๐ข๐ฑ ๐‚๐จ๐ง๐ฌ๐จ๐ซ๐ญ๐ข๐ฎ๐ฆ, participation in APCOM 2025 provided invaluable opportunitiesโ€”not only through peer review of our analytical models but also via knowledge transfer of advanced solutions that support our analytics development and offering processes. The program featured over ๐Ÿ–๐ŸŽ ๐ฉ๐ž๐ž๐ซ-๐ซ๐ž๐ฏ๐ข๐ž๐ฐ๐ž๐ ๐ฉ๐š๐ฉ๐ž๐ซ๐ฌ, training sessions, workshops, and expert panels, delivering a knowledge exchange and training level comparable to the worldโ€™s top industry events.
Representing the ๐’๐ฒ๐ฌ๐ญ๐ž๐ฆ ๐€๐ง๐š๐ฅ๐ฒ๐ญ๐ข๐œ๐ฌ ๐ƒ๐ž๐ฉ๐š๐ซ๐ญ๐ฆ๐ž๐ง๐ญ ๐š๐ญ KGHM CUPRUM sp. z o.o. – Centrum Badawczo-Rozwojowe, dr hab. eng. Paweล‚ Stefaniak (Habilitated Doctor of Engineering) and MSc Eng. Maria Stachowiak presented research results conducted within the NetHelixEU ๐ฉ๐ซ๐จ๐ฃ๐ž๐œ๐ญ, delivering ๐ญ๐ก๐ซ๐ž๐ž ๐ญ๐ž๐œ๐ก๐ง๐ข๐œ๐š๐ฅ ๐ฉ๐š๐ฉ๐ž๐ซ๐ฌ:
1๏ธโƒฃMonitoring-based optimization of Horizontal Transport in Underground Mines Using Machine Learning and Data Integration from NGIMU sensors.
2๏ธโƒฃOptimization of Mining Machinery Maintenance in Modern Mining Enterprises through Text Mining and Machine Learning Techniques
3๏ธโƒฃReal-Time Monitoring and Machine Tracking in Large-Scale Underground Mines Using Safety Systems and Machine Learning Techniques
The NetHelix project demonstrates how interdisciplinary collaboration across research institutions and industry can lead to innovation in reliability modeling, system network analysis, and predictive mining operations.
A big thank-you to all our consortium partners โ€” your contribution is making an international impact! ๐Ÿ‘๐ŸŒ

 

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