OPTIMIZATION MODEL FOR SELECTING LOADING AND HAULING EQUIPMENT IN OVERBURDEN REMOVAL ACTIVITIES AT PIT PS PT. XYZ - Ramdhani, Bintang
In mining activities, one of the main focuses of the activity is the cost component incurred by a company to carry out production operations. The cost components that are often used to measure the costs that companies must incur to carry out mining activities are owning costs and operating costs. This study was conducted to calculate and analyze the needs of loading and hauling equipment that will be used by PT XYZ to achieve the Company's expected overburden removal production target based on the availability of existing equipment but with the minimum costs incurred. For this reason, linear program modeling using python is carried out to produce optimal loading and hauling equipment requirements. The availability of loading equipment owned by PT XYZ is 1 unit of Liebherr 996 (32 m3), 3 units of Liebherr 996 (36 m3), and 3 units of Hitachi EX3600. While the availability of hauling equipment is 20 units of Caterpillar 789B, 8 units of Caterpillar 789D, 7 units of Euclid Hitachi 3500, and 19 units of Euclid Hitachi 4500. This research employed two methods: optimization using linear programming and the trial & error method, with constraints such as production targets, match factors, and equipment availability. The calculation results showed that optimization using linear programming could determine the equipment requirements more optimally than trial & error method. Optimization using linear programming requires 4 units of loading equipment, with details of 1 unit of Liebherr 996 (32 m3), 1 unit of Liebherr 996 (36 m3), and 2 units of Hitachi EX3600 while for hauling equipment it requires 20 units of Caterpillar 789B, 5 units of Caterpillar 789D , 1 unit of Euclid Hitachi 3500 and 19 units of Euclid Hitachi 4500 with a total of 45 units of hauling equipment. This results in optimization being able to reduce the use of transportation equipment by 6 units less than the results of trial & error and the costs incurred per hour for production operations are $3,767.06 less than the costs required using the trial & error method.