An Investigation of Diggability and Other Digging Effort Related Metrics for Cable Shovels at Multiple Mines
Branscombe, Edward A.
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A performance monitoring study was conducted aboard electric cable shovels at three different open-pit mines for the purposes of quantifying digging effort. A comparative analysis of public domain diggability metrics was conducted to look at the influence of rock types, fragmentation distribution, blasting practices, excavator capabilities and other factors on calculated values. Results showed that fragmentation size distribution and excavator capabilities (power and size) influenced shovel behaviour significantly, resulting in public domain diggability metrics to be non-representative of digging conditions at some sites. Further analysis of performance monitoring data demonstrated that energy consumption monitoring was representative of digging conditions at sites where public domain diggability metrics failed. All shovels in this study were excavating in blasted, hard rock environments. Concurrent research analyzed the sensitivity of the calculated metrics to dig cycle timing inaccuracies and the degree to which these timing inaccuracies affected the calculated values of each performance metric. The importance of accurately identifying the dig state and all other possible shovel states is discussed for the purpose of data set integrity and accurate productivity monitoring. The main focus for this aspect of the research is the positive identification of the clean-up actions which were found to be infrequent at some sites and commonplace at other sites. These clean-up actions were analyzed for their energy consumption and were discovered to be a non-trivial component of total energy use. Operator influence on calculated metrics was observed and analyzed for each mine site with particular attention paid to unique operator joystick behaviour. A guideline for the application of diggability metrics is given and focuses on fragmentation distribution and blast performance as well as excavator power and size as the determining factors between the use of energy consumption as a metric and the use of the previously established ‘diggability indices’ for the representation of digging conditions. New methods for visualization of metrics as well as data averaging and smoothing techniques are presented to interpret performance monitoring results in various ways and to help identify trends in the data.