TY - GEN
T1 - Fusion of operations, event-log and maintenance data
T2 - 10th International Conference on Condition Monitoring, CM 2013 and Machinery Failure Prevention Technologies 2013, MFPT 2013
AU - Naeem, Hassan Bin
AU - Mainali, Ganesh
AU - Johansson, Carl Anders
AU - Galar, Diego
PY - 2013
Y1 - 2013
N2 - The modern mining industry is highly mechanised and relies on massive, multimillion-dollar pieces of equipment to achieve production targets. In an increasingly challenging international economic climate, mining operations are reliant on economies of scale to remain competitive. To maximise revenue, it is imperative that at each stage of the mining process, equipment is operating optimally without preventable and unnecessary interruptions. As a result, the focus of all mining operations is to increase equipment uptime and utilisation. The data used for this investigation have been sourced from the Aitik mine, a large open pit copper mine in Northern Sweden. In the loading area, power shovels load trucks with blasted material for transport, either to the crushers or to the waste dumps. The Aitik mine employs various computer-aided applications to track and maintain mobile mining equipment like the shovels. These applications also serve as chronological operational and maintenance databases for the equipment. This paper's study of six mining shovels is based on the analysis of three data types: historical maintenance data from CMMS Maximo, operational data from mine management system Cat® MineStar™, and event-log data from individual shovels. The results indicate that such a synthesis is viable. A regular time-lapse integration of the diverse data types displays potential and could prove helpful in achieving overall improvements in maintenance.
AB - The modern mining industry is highly mechanised and relies on massive, multimillion-dollar pieces of equipment to achieve production targets. In an increasingly challenging international economic climate, mining operations are reliant on economies of scale to remain competitive. To maximise revenue, it is imperative that at each stage of the mining process, equipment is operating optimally without preventable and unnecessary interruptions. As a result, the focus of all mining operations is to increase equipment uptime and utilisation. The data used for this investigation have been sourced from the Aitik mine, a large open pit copper mine in Northern Sweden. In the loading area, power shovels load trucks with blasted material for transport, either to the crushers or to the waste dumps. The Aitik mine employs various computer-aided applications to track and maintain mobile mining equipment like the shovels. These applications also serve as chronological operational and maintenance databases for the equipment. This paper's study of six mining shovels is based on the analysis of three data types: historical maintenance data from CMMS Maximo, operational data from mine management system Cat® MineStar™, and event-log data from individual shovels. The results indicate that such a synthesis is viable. A regular time-lapse integration of the diverse data types displays potential and could prove helpful in achieving overall improvements in maintenance.
KW - Data fusion
KW - Maintenance management
KW - Mining shovels
UR - https://www.scopus.com/pages/publications/84905870074
M3 - Conference contribution
AN - SCOPUS:84905870074
SN - 9781629939926
T3 - 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013
SP - 484
EP - 503
BT - 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013
PB - British Institute of Non-Destructive Testing
Y2 - 18 June 2013 through 20 June 2013
ER -