The case study consist of a small underground mine with a small mining crew. The vehicle park is relatively large, and therefore it is necessary to establish the added value of additional miners or equipment for short-term production planning purposes, assuming that staff size currently limits production capacity to find out if staff size is indeed the bottleneck in the production capacity of the mine operation. When the bottlenecks of the mining system are known, it will be easier to focus on necessary areas and further implementations to improve the system.

The truck numbers used in the simulation study were ranging from 4 to 7, and the operator pool size was ranging from 10 to 15 people. Significant findings of this study are that with the current mine setup of 4 trucks, there would be no increase in production when adding operators. For the 24 scenarios the production increase was determined, the revenue change and the mining cost. By adding trucks and operators, a production increase of 19.38 % could be reached with 15 operator and 7 trucks.

Blasting and drilling serves as an essential element for a mining operation to excel. Optimization of this operational aspect, requires consideration of various parameters that can be controllable or uncontrollable. To overcome the tediousness of analyzing each element selectively, some major parameters are outlined, and each blast is rendered relative to the other, by organizing the data from each blast design and integrating it in an empirical model called Kuz-Ram Model, which further can be used for predicting the impact of these parameters on fragmentation. Image analysis aids in validating the model credibility for using it as step forward for proposing alterations to the current practices in drilling and blasting area. Each image is processed with the help of Unmanned Aerial Vehicle, for safety and coverage of complete muck-pile. The study involves in depth focus on the impact of rock mass characteristic over fragmentation as well. Discontinuities, fractures, joint orientation and fillings are considered in designating each rock zone to specific class with the help of a geo-mechanical classification system called, Rock Mass Rating. To test the theory, an exercise is performed by separating two zones of variable rock mass properties and then the procedure is followed with empirical calculation, image analysis and supported by preferential loading to acquire a broad image of each zone fragmentation profile. Suggesting the variation in particle size distribution due to rock mass influence. The collected data and analyses shall serve as supporting tools for changes to blast design for obtaining desired fragmentation, which is synonymous to increasing the feed of kilns.