{"id":56367,"date":"2026-04-22T07:09:00","date_gmt":"2026-04-22T04:09:00","guid":{"rendered":"https:\/\/geoconversation.org\/news\/ai-at-lebedinsky-gok-raised-dump-truck-utilization-by-4-and-increased-ore-shipments\/"},"modified":"2026-04-22T08:53:42","modified_gmt":"2026-04-22T05:53:42","slug":"ai-at-lebedinsky-gok-raised-dump-truck-utilization-by-4-and-increased-ore-shipments","status":"publish","type":"news","link":"https:\/\/geoconversation.org\/en\/news\/ai-at-lebedinsky-gok-raised-dump-truck-utilization-by-4-and-increased-ore-shipments\/","title":{"rendered":"AI at Lebedinsky GOK raised dump truck utilization by 4% and increased ore shipments"},"content":{"rendered":"\n

Metalloinvest specialists noticed a disturbing pattern: during night shifts at Lebedinsky Mining and Processing Plant, dump trucks were leaving the open pit with underloads. The lag from the daytime figures reached 4%. The reason was not in the equipment, but in the human factor – at night the control over loading is weaker. <\/p>\n\n

Instead of increasing human supervision, the mill decided to entrust the control to artificial intelligence<\/a>. Video cameras connected to the AI system were installed on the four crusher ramps of the transshipment center. Now, as soon as a dump truck pulls in for unloading, the neural network scans its body and instantly checks the volume of rock against the standards. <\/p>\n\n

If the AI detects underloading, it determines which excavator loaded the machine and automatically sends a notification to the excavator driver, shift foreman and site manager. Recognition accuracy has reached 98%. Thanks to this, violations are corrected right during the shift, without waiting for morning reports. <\/p>\n\n

The result of the implementation exceeded expectations. Starting from December 2025, the transshipment point complex has been consistently shipping about 3 million tons of ore per month to the concentrator. Previously, this figure fluctuated between 2.6 and 2.8 million tons. It was video analytics that provided the increase – without purchasing new dump trucks or excavators. <\/p>\n\n

Lebedinsky GOK, a member of the Russian Mining Industry Association, has once again demonstrated: digital technologies are capable of delivering rapid measurable productivity growth. Artificial intelligence<\/a> does not replace people, but helps them work more efficiently – especially where attention is inevitably scattered.<\/p>\n\n

Source: @gorprom<\/p>\n\n

Image: Metalloinvest<\/p>\n","protected":false},"excerpt":{"rendered":"

Metalloinvest specialists noticed a disturbing pattern: during night shifts at Lebedinsky Mining and Processing Plant, dump trucks were leaving the open pit with underloads. The lag from the daytime figures reached 4%. The reason was not in the equipment, but in the human factor – at night the control over loading is weaker. Instead of […]<\/p>\n","protected":false},"author":12,"featured_media":56374,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"","_seopress_titles_title":"AI video analytics at Lebedinsky GOK increased dump truck utilization rate","_seopress_titles_desc":"A neural network scans the body and notifies of underloading with 98% accuracy. Learn how it helped increase ore shipments to 3 million tons per month. ","_seopress_robots_index":"","footnotes":""},"categories":[572],"tags":[574,573],"class_list":{"0":"post-56367","1":"news","2":"type-news","3":"status-publish","4":"has-post-thumbnail","6":"category-it","7":"tag-artificial-intelligence-in-geology","8":"tag-automation-and-robotization"},"acf":[],"pbg_featured_image_src":{"full":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii.webp",1280,853,false],"thumbnail":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-150x100.webp",150,100,true],"medium":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-300x200.webp",300,200,true],"medium_large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-768x512.webp",768,512,true],"large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-1024x682.webp",1024,682,true],"1536x1536":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii.webp",1280,853,false],"2048x2048":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii.webp",1280,853,false],"bricks_large_16x9":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-1200x675.webp",1200,675,true],"bricks_large":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-1200x800.webp",1200,800,true],"bricks_large_square":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-1200x853.webp",1200,853,true],"bricks_medium":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-600x400.webp",600,400,true],"bricks_medium_square":["https:\/\/geoconversation.org\/wp-content\/uploads\/2026\/04\/skanirovanie-kuzova-ii-600x600.webp",600,600,true]},"pbg_author_info":{"display_name":"Yulia Frolova","author_link":"https:\/\/geoconversation.org\/en\/author\/giulia-nikolaevna\/","author_img":false},"pbg_comment_info":" No Comments","pbg_excerpt":"Metalloinvest specialists noticed a disturbing pattern: during night shifts at Lebedinsky Mining and Processing Plant, dump trucks were leaving the open pit with underloads. The lag from the daytime figures reached 4%. The reason was not in the equipment, but in the human factor – at night the control over loading is weaker. Instead of…","_links":{"self":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/56367","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news"}],"about":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/types\/news"}],"author":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/comments?post=56367"}],"version-history":[{"count":1,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/56367\/revisions"}],"predecessor-version":[{"id":56376,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/news\/56367\/revisions\/56376"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/media\/56374"}],"wp:attachment":[{"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/media?parent=56367"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/categories?post=56367"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geoconversation.org\/en\/wp-json\/wp\/v2\/tags?post=56367"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}