Scholarly record
SIMULATION OF DRILLING OPERATIONS
Abstract
Mine design is dependent upon two categories of data as layout and operations. Layout data are related mainly with the geomechanical and geometrical properties of ore and rock masses. This group of data has an effect to define the geometrical variables of the layout and the operating characteristics of the possible system. Mine design processes suffer mainly from obtaining reliable and adequate data. Operational research methods have been extensively assisted by design engineers to overcome the difficulties related to the quality and the amount of the data available. Among these methods, simulation is used generally in process modelling and produces valuable information related to the performances of the possible system. The method allows generating reliable estimates under the condition of limited data and can be used to develop alternative scenarios in modelling mining processes. This paper introduces a drilling simulation model and software that can be used in sublevel stoping applications. The model is capable of simulating drifting operations employed in development and production sequences. It is able to generate data to estimate productivity and operating costs of drilling operation.
Publication details
References23
and the site observations [15] . Modeler can assign values for each operation related variables.
EVALUATION OF MODEL An interactive simulation software was developed to implement the model described in the previous sections. The simulation software, in fact, was constructed as part of a complete production system modeling software of the sublevel stoping mining method. It was developed using C programming language. Since a discrete event time simulation modeling is used in the simulation, the major variables defining the activity in each event are identifie d by a statistical distribution model. The modeler can define values and statistical distributions (or related statistical parameters) for the event variables. As default, the model performs simulations employing uniform distributions. The model produces various data to be used to calculate performance or productivity data. This group of data is related to the duration of the special events, or processes, in the operation. In Figure 4, a screen capture shoving the data kept during simulation routine has been illustrated. Figure 4. The major operating variables generated for the drilling operation. A hypothetical model was used to assess the model. Below given are the major drilling pattern and equipment variables. Drilling Pattern: Parallel Cut Length of Holes (cut/stoping/empty): 4400 mm. Number of Stoping Holes: 27 Diameter of Stoping Holes: 38 mm. Number of Cut Holes: 16 Diameter of Cut Holes: 38 SGEM 200 6 - Section I 59 Diameter of Empty Hole: 102 mm Rock Drillability Index: 70 Road Rolling Resistance: 3% Grade of Road: Tree segment road, one segment has 12o down grade Drilling Units: One 1 x 16 kW Jumbo, one 2 x16 kW jumbo The results obtained using different drilling units have been illustrated on Table 2. The values given in columns 1 and 2 are obtained by the same machi nes, but different round numbers. Given in 3rd column are the results obtained by a 2 drill machine. Table 2. Simulation results using different drilling units. Drill Number x Drill Power
x 16 kW 1 x 16 kW 2 x 16 kW Round Simulated 15 50 15 Tram ming Distance 4139.920, sec. 14071.167, sec. 4139.920, m. Tramming Time 3486.251, sec. 10749.143, sec. 3528.424, sec. Machine -Face Prepare Time
705, sec. 15630.383, sec. 4690.820, sec. Drilling Time Ordinary* Holes
797,sec. 402968.062,sec. 60451.891, sec. Drilling Time of Empty Holes
195, sec. 121993.086 sec. 36600.938, sec. Ordinary* Hole Meters
000, m. 8800.000, m. 2640.000, m. Empty Hole Meters 660.000, m. 2200.000, m. 660.000, m. Hole Drilling Time 157600.984,sec. 524961.12 5,sec. 97052.828, sec. Machine Stowing Time
852, sec. 7815.711, sec. 2331.410, sec. Total Round Time 168178.969,sec. 559156.312,sec. 107617.477,sec. * includes the total of cut and stoping holes The statistics given in above table can also be used in cost estimation process. A cost estimation module was developed and to be integrated in the total simulation package intended.
RESULTS Simulation can be seen as a tool to experiment with the design of an engineer. It can be a valuable tool in the design work of the mining engineers, since he/she faces some difficulties in estimating performance of the possible system. Using a simulation model/software alternative operating scenarios can be developed for the system to be designed. Having identified the conditions to affect the system, suitable operating variables and the flexibilities in case of adverse conditions can be identified. The drilling simulation model developed can be used to model drilling operations in drifting. The model and therefore the software can be used for two purposes as modeling of the drilling operation and selection of the drilling machine. When using for the operation model generating aim, it can generate detailed statistics to estimate both 6th International Multidisciplinary Scientific GeoConference SGEM2006 www.sgem.org Int er nat ional Confer ence SGEM 200 6 60 productivity and cost. On the other hand, the drilling machine selection can be done using the software. It is capable of simulating 1 to 4 drill jumbos. REFERENCES
Sturgul, J. R., 1996, History and annotated bibliography of mine system simulation. Proc. 1st Int. Symp. on Mine Simulati on via the Internet and Cyber Space , Athens,
Sturgul J. R., 1995, Simulation and animation -come of age in mining, Engineering and Mining Journal , 196, 38-42.
Mutagwaba, W.K. and J.A. Hudson., 1993, Use of object -oriented simulation model to asses operating and equipment conditions for underground mine transport system, Trans. Inst. Min. and Metallurgy: A, 102, A89-94.
Mutagwaba, W.K., and S. Durucan, 1994, A three phase simulation model for mine transport analysis. Proc. ‘Mine Planning and Equipment Selection , Istanbul, 289-
Zaiking, L., 1996, Computer simulation and its application in the extraction, conveyance and hoisting system of coal mines. Proc.26 th APCOM , Pennsylvania,
Lebedev A.A., 1998Staples P., Simulation of materials handling systems in the mines: Two Case Studies, Simulation , 70, , 183 -196
McNearny R.L; and Nie Z.S., 2000, Simulation of a conveyor belt network at an underground coal mine, Mineral Resources Engineering , 9, 343 -355.
Runciman N; Vagenas N; Corkal T., 1997, Simulation of haulage truck loading techniques in an underground mine using WITNESS, Simulation , 68, 291-299.
Frimpong S., 1995, Whiting J.M., Constrained simulation of a mine production system, Simulation , 65, 305-312.
Vagena s N., 1996, Simulation modeling of a fleet of remote -controlled automatic load -haul-dump vehicles in underground mines, Simulation , 67, , 331-342.
Vagenas N, 2000, Scoble, M., Corkal, T. and Baiden, G., Simulation of teleremote mining systems, CIM Bulletin , 93, 61-64.
Runciman, N and Vagenas, N., Evaluation of underground drill and blast systems using discrete -event simulation, Mineral Resources Engineering , 7, 1998, 211-220.
Tamrock, Handbook of underground drilling. (Tamrock, Tampere, 1983). 14] Roos, H. H., 1987, Percussion Drill Jumbos , in “Underground Mining Methods Handbook”, W.A. Hustrulid, ed., SME -AIME, pp. 1034-1049, New York.
CBI, 1999, Site observations was made in 1998 and 1999. 6th International Multidisciplinary Scientific GeoConference SGEM2006 www.sgem.org
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.
