Optimization of Heavy Equipment Capabilities in The Framework of Productivity and Coal Mining Business Sustainability: Case Study of East Kalimantan Mining Area

Coal mining business is now faced with various challenges such as export restrictions policy, an increase in value added products, and the decline in market prices of products. To be able to compete, mining companies are expected to increase productivity and efficiency and make continuous improvemen...

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Bibliographic Details
Published inIDEAS Working Paper Series from RePEc
Main Authors Quarm, Richmond Sam, Busharads, Mohamed Osman Elamin, Sam-Quarm, Richmond, Institute of Research, Asian
Format Paper
LanguageEnglish
Published St. Louis Federal Reserve Bank of St. Louis 01.01.2020
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Summary:Coal mining business is now faced with various challenges such as export restrictions policy, an increase in value added products, and the decline in market prices of products. To be able to compete, mining companies are expected to increase productivity and efficiency and make continuous improvements in the production process. In the mining process, the availability of equipment and dump truck unloading tool will determine the sustainability of production that have an impact on productivity and efficiency. The purpose of this study was to optimize the production of coal mining in the context of the efficient use of equipment using the match factor, queues, and linear programming. The research location is in the area of the mining concession contractor KTD Corp is in the village of Embalut, District Tenggarong Seberang, Kertanegara Kutai Regency, East Kalimantan in October-November 2015. Unloading equipment used backhoe excavator is 5 units and 32 units of dump trucks. The simulation results match factor generated by the method optimal dump truck needs 26 units, while the queuing method and linear programming as much as 25 units of dump truck. The results of production optimization with linear programming method produced mining productivity of 1,208 BCM of overburden per hour with the optimum cost of $ 0,909/BCM.
DOI:10.31219/osf.io/gtfqj