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Wskazówki dla autorów Archiwum
2019 vol. 26
POPRZEDNI NASTĘPNY
CC BY-NC 3.0 Polska
 
 

A DATA DRIVEN DECISION MAKING APPROACH FOR LONG-WALL MINING PRODUCTION ENHANCEMENT

Amid Morshedlou 1,  
Hesam Dehghani 1  ,  
Hadi Hoseinie 2
 
1
Hamedan University of Technology
2
Isfahan University of Technology
Mining Science 2019;26:7–20
DOI: https://doi.org/10.37190/msc192601
Statystyki Artykuł (PDF, 208.64 kB)
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Referencje (27)
 
SŁOWA KLUCZOWE
reliability, Maintenance, longwall system, production risk
DZIEDZINY
Technologia eksploatacji podziemnej i odkrywkowej złóż, Projektowanie i budowa kopalń oraz budownictwo podziemne
STRESZCZENIE ARTYKUŁU
Machine failures have destructive effects on continuity of operation and lead to production losses in long-wall mines, making proper maintenance scheduling essential. This paper models the reliability of the whole production chain in an Iranian long-wall mine including the drum shearer, Armored Face Conveyor (AFC), hydraulic powered supports, Beam Stage Loader (BSL), and main conveyer belt. Analyzing the computational results and failure frequencies, we rank the critical components and develop a reliability-based preventive maintenance schedule for all equipment. In respect to the data classification, conveyor belt with failure abundance of 41.5 percent is the most critical, while powered supports with the failure abundance of 1.2 percent shows the best performance. Approximately, the reliability of the production process after four hours reaches nearly to zero. Implementing the schedule, computational results suggest an increase of approximately 67.7 percent in the average production per shift.
AUTOR DO KORESPONDENCJI
Hesam Dehghani   
Hamedan University of Technology
 
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