An Integrated Multi Objective Multi Stage Mining Fleet Management System Linking Dynamic Operation to Short-Term Plan

"Fluctuation in market price of mineral products has enforced mining companies to cut down their operating costs. One useful way of reducing operating costs in mining operations is to make optimal operational decisions, incorporating efficient mining fleet management systems (FMS). Over the last 50 years, several types of FMS have been developed and introduced in the mining systems around the world. However, there are two major shortcomings in existing systems. Firstly, none of the existing systems consider effects of the short-term plan on dynamic truck assignment. Secondly, most of the existing FMSs make decisions in a way that optimize a specific objective while ignoring others. Herein, we propose a multi stage and multi objective FMS that deals with aforementioned shortcomings of the currently available systems. The developed FMS, in its upper stage, links semi-dynamic operational decision making process to the short-term production plan by simultaneously assigning shovels to mining faces and allocating trucks to the shovels by implementing its first multi objective decision making model. Then in its second stage, in a real time dynamic decision making process, it assigns trucks to shovels and corresponding destinations by optimizing its second multi objective decision making model. The developed fleet management system has been verified using an Iron ore case study and the results are presented in this paper. INTRODUCTION Open pit mining method is the most common method to mine mineral from the earth. Based on Wetherelt and van der Wielen (2011) there exist 2500 open pit metal mines that are categorized as industrial scale mines. Over all of those, the amount of material handled using truck and shovel material handling system is more than the amount handled by all other systems together (Humphrey & Wagner, 2011).It has been proven by several studies that more than 50 percent of operating cost in a truck and shovel based open pit mining operation is accounted for material handling (Moradi Afrapoli & Askari-Nasab, 2017, Alarie & Gamache, 2002, Ahangaran et al., 2012). Thus, introducing even 1 to 2 percent cut in its material handling cost saves huge amount of money for the stakeholders. Over the last 50 years, two major areas have been identified to cut this cost. On one hand mining industries have been implementing equipment with higher production capacities, and on the other hand, researchers have been developing operations research techniques to make dynamic decisions as close to optimal as possible to deduct operational costs in truck and shovel based mining operations."