## 2 Methodology
### Development of the Calibration Model  
The methodology proposed by numerous authors recommends following the next steps [29; 30; 31]. Step 1. Gathering existing information and generation of probabilistic distribution functions. Enough information related to the variables that intervene in the loading and hauling processes had to be gathered. Those variables included the tonnages loaded by existing equipment in the mine, fixed times of the cycle time, topographies, haul roads, and operating delays in the operation. Part of the previous information was obtained from a report generated by the CAT MineStar System. With the gathered information loaded in text (txt) format, the probabilistic distribution functions (PDF), density functions of the fixed times, and loaded tonnages were generated through Arena Input Analyzer, which helped to obtain distributions that fit the sample data. [PERSON] [29] and [PERSON] et al. [4] described the analysis and modeling of the collected information in detail. The distributions were evaluated based on the Chi-square and Kolmogorov-Smirnov tests (KS) since Arena works with those tests to measure the goodness of the fit [2,10]. Regarding the variable times, mean values were chosen and obtained from the truck velocities according to the road grade and from the traveled distances. The traveled distances were calculated with the Dijkstra algorithm, whose objective is to obtain the shortest distance between two points. Step 2. Creation and calibration of the model. With the distribution functions of the fixed times and tonnages and the mean values of the variable times, processes and entities were created in the calibration model in Arena software. Furthermore, the target tonnages for the daily model were introduced as inputs. The steps taken to create the calibration model are presented in the following flowchart (Figure 1). In the loading and hauling process, trucks arrive at the loading areas where a shovel or FEL is rehandling either ore, stock, or waste material. These trucks are configured in Arena Software as entities, and they are assigned in groups to a fixed piece of loading equipment. Furthermore, each of the processes shown in Figure 1 is created in Arena following the order mentioned in the flowchart. At the beginning of the haul cycle, trucks might be queuing at the loading front or spotting if no other truck is present. Once the truck has spotted, the shovel or FEL might be ready to release the material onto the truck bed, which will depend on the available material. Depending on the loaded material, trucks might travel to the crusher, stockpile, or waste dump. After the loaded trucks arrive at their destination, they might queue or spot to finally release their material. Later, the haul cycle comes to an end, with the empty truck returning to the fixed loading front. At the end of the cycle, a delay time is added, which replicates operating stoppages happening in the mine. Arena Software allows the user to save the results from each process in atxt format, which is later processed through an Excel spreadsheet. Moreover, the calibration model did not consider truck stoppages for corrective maintenance or preventive maintenance; consequently, the entire truck fleet was always available. Other activities that did not factor into the calibration model were no operators available, limitations in the crushing rates, and lack of trucks. Finally, loading equipment applied the FIFO rule-- first in, first out--which meant that the first truck arriving at the loading zone was given priority. Step 3. Validation of results. After the creation of the calibration model in Arena, the model was run, and the results obtained from it were compared with the real values from the Operations Team. The evaluated parameters were loaded tonnages by loading equipment, and total production.