Optimising Shovel-Truck Fuel Consumption using Stochastic Simulation

Authors

  • Nelson Kofi Dumakor-Dupey University of Mines and Technology

Keywords:

Simulation, Fuel Consumption, Optimisation, Arena®, Shovel-Truck

Abstract

Fuel consumption of loading and hauling equipment contributes significantly to the operating cost of a mining enterprise. Hence, it is imperative to periodically analyse the operations of shovel-truck system to identify system inefficiencies and develop effective means of reducing fuel consumption. In this paper, a stochastic simulation model to analyse the fuel consumption of a shovel-truck system is proposed. The model is developed using the Arena® Software. The average monthly fuel consumption by the digging and excavating equipment is found to be 62 000 litres at 95% confidence interval, reflecting a variance of -3.8% from the actual fuel consumption (64 362 litres). Optimising fuel consumption by the trucks will result in monthly fuelsavings of 3283 litres. It is also recognised that a total of about 22 000 litres of fuel is consumed per month due to truck waiting. It is anticipated that greater fuel savings will be achieved if the entire shovel-tuck systems of the mine is optimised. The paper also demonstrates that stochastic simulation is an effective tool for optimising the utilisation of fossil-based fuels in mining and related industries.

Author Biography

Nelson Kofi Dumakor-Dupey, University of Mines and Technology

University of Mines and Technology

Mining Engineering Department

Demonstrator

References

Adak, P., Sahu, R. and Elumalai, S. P. (2016), “Development of Emission Factors for Motorcycles and Shared Auto-rickshaws Using Real-world Driving Cycle for a typical Indian Cityâ€, Science of The Total Environment, Vol. 544, pp. 299-308.

Altiok, T. and Melamed, B. (2007), Simulation Modeling and Analysis with Arena, Elsevier Academic Press, New York, USA, 440pp.

Anglani, A., Grieco, A., Pacella, M., andTolio, T. (2002), “Object-Oriented Modelling and Simulation of Flexible Manufacturing Systems: A Rule-based Procedureâ€, Simulation Modelling Practice and Theory, Vol. 10, Issue 3, pp. 209-234.

Awuah-Offei, K. (2012), “Can Discrete Event Simulation Help You Improve Your Operation?â€http://sphinxminingsystems.com/blog/?p=78. Accessed: January 30, 2015.

Awuah-Offei, K., Osei, B. and Askari-Nasab, H. (2012), “Improving Truck-Shovel Energy Efficiency Through Discrete Event Modelingâ€, Society of Mining, Metallurgy & Exploration (SME) Annual Meeting, Seattle, WA., Preprint 12-069, pp. 1 – 6

Fioroni, M. M., Bianchi, T. J., Pinto, L. R., Franzese, L. A. G., Luiz Ezawa, L. and Miranda, G. (2008), “Concurrent Simulation and Optimization Models for Mining Planningâ€, Proceedings of the 2008 Winter Simulation Conference, Mason, S. J. (ed.), Florida, USA, pp. 759 – 767.

Heide, C. H. and Mohazzabi, P. (2013), “Fuel Economy of a Vehicle as a Function of Airspeed: The Concept of Parallel Corridorsâ€, International Journal of Energy and Environmental Engineering, 2013, pp. 1 – 9.

Hogg, G. A., Pulkki, R. E. and Ackerman, P. A. (2010), “Multi-stem Mechanized Harvesting Operation Analysis–Application of Arena 9 Discrete-event Simulation Software in Zululand, South Africaâ€, International Journal of Forest Engineering, Vol. 21, Issue 2, pp.14-22.

Jun, J. B., Jacobson, S. H. and Swisher, J. R. (1999), “Application of Discrete-event Simulation in Health Care Clinics: A Surveyâ€, Journal of the Operational Research Society, pp. 109-123.

Kecojevic, V. and Komljenovic, D. (2010), “Haul Truck Fuel Consumption and CO2 Emission under Various Engine Load Conditionsâ€, MınıngEngıneerıng Magazine, December, 2010, pp. 44 – 48.

Koellner, W. G., Brown, G. M., Rodríguez, J., Pontt, J., Cortés, P. and Miranda, H. (2004), “Recent Advances in Mining Haul Trucksâ€, Industrial Electronics, IEEE Transactions, Vol. 51, Issue 2, pp. 321-329.

Koenig, R. L., Marinopoulos, N. and Olsson, B. R. (2002), “Using Reliability Modelling to Confirm Plant Design Capacityâ€, Proceedings of Metallurgical Plant Design and Operating Strategies, Sydney, NSW, pp. 248 - 260.

Komashie, A. and Mousavi, A. (2005), “Modeling Emergency Departments Using Discrete Event Simulation Techniquesâ€, In Proceedings of the 37th conference on Winter simulation, Winter Simulation Conference, pp. 2681-2685.

Krause, A. and Musingwini, C. (2007), “Modelling Open Pit Shovel-Truck Systems Using the Machine Repair Modelâ€, The Journal of The Southern African Institute of Mining and Metallurgy, Vol. 107, August 2007, pp. 469-476.

Kuhl, M. E., Kistner, J., Costantini, K. and Sudit, M. (2007), “Cyber-Attack Modelling and Simulation for Network Security Analysisâ€, In Proceedings of the 39th Conference on Winter Simulation, December, IEEE Press, pp. 1180-1188.

Kumar, S. and Phrommathed, P. (2006), “Improving a Manufacturing Process by Mapping and Simulation of Critical Operationsâ€, Journal of Manufacturing Technology Management, Vol. 17, Issue 1, pp. 104-132.

Li, S., Dimitrakopoulos, R., Scott, J. R. and Dunn, D. (2004). “Quantification of Geological Uncertainty and Risk using Stochastic Simulation and Applications in the Coal Mining Industry†In Orebody Modelling and Strategic Mine Planning-Uncertainty and Risk Management International Symposium 2004, The Australasian Institute of Mining and Metallurgy, pp. 185-192.

Lin, H., Cui, X., Yu, Q. and Yang, S. (2011), “Experimental Study on Diesel Vehicle’s Fuel Consumption Feature While Coasting on Level Roadâ€, Proceedings of International Conference, Part 1, CSIE 2011, Shen, G. and Huang, X. (eds.), Zhengzhou, China, 21 - 22 May, 2011. pp 264 – 270.

Nel, S., Kizil, M. S. and Knights, P. (2011), “Improving Truck-Shovel Matchingâ€, Proceedings of the 35th APCOM Symposium, Wollongong, NSW, pp. 381 – 391.

Norgate, T. and Haque, N. (2010), “Energy and greenhouse gas impacts of mining and mineral processing operationsâ€, Journal of Cleaner Production, Vol. 18, Issue 3, pp. 266-274.

Parreira, J. (2013), “An Interactive Simulation Model to Compare an Autonomous Haulage Truck System with a Manually-Operated Systemâ€, Unpublished Doctoral Dissertation, University of British Columbia, Vancouver, 212pp.

Patil, K., Jin, K. and Li, H. (2011), “Arena Simulation Model for Multi Echelon Inventory System in Supply Chain Managementâ€, In Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference, December, IEEE, pp. 1214-1217.

Rogers, P. (2002), “Optimum-Seeking Simulation in the Design and Control of Manufacturing Systems: Experience with OptQuest for Arenaâ€, In Simulation Conference, 2002. Proceedings of the Winter, December, IEEE, Vol. 2, pp. 1142-1150.

Shelswell, K. J., Fitzgerald, J. and Labrecque, P. O. (2013), “Discrete Event Simulation Modelling versus TKM Analysis of a Mine Operating with a Hybrid Material Movement Practice Consisting of Truck Haulage and Skippingâ€, Proceedings of CIM Convention, Toronto, 2013, 9pp.

Siami-Irdemoosa, E. and Dindarloo, S. R. (2015), “Prediction of Fuel Consumption of Mining Dump Trucks: A Neural Networks Approachâ€, Applied Energy 151, pp. 77–84.

Wang, T., Guinet, A., Belaidi, A. and Besombes, B. (2009), “Modelling and Simulation of Emergency Services with ARIS and Arena. Case Study: The Emergency Department of Saint Joseph and Saint Luc Hospitalâ€, Production Planning and Control, Vol. 20, Issue 6, pp. 484-495.

Zeng, Q. and Yang, Z. (2009), “Integrating Simulation and Optimization to Schedule Loading Operations in Container Terminalsâ€, Computers & Operations Research, Vol. 36, Issue 6, pp. 1935-1944.

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Published

2017-12-20