# Digitalization in Open-Pit Mining: A New Approach in Monitoring and Control of Rock Fragmentation
## 4 Results and Discussion
According to the algorithm presented in Figure 3, the authors have developed a program that allows the fragment form parameter and its distribution to be obtained from photographs of blasted rock mass. Figure 14 shows the interface of the software that allows the form distribution to be determined. This fragment shows one of the steps of the algorithm in Figure 3. In this step, the user is prompted to select the eight squares in the figure and confirm their actions. Everything occurs in manual mode--a photo is loaded, and the user marks the eight squares  
Figure 13: Fragment form distribution by fractions for the 1 st stage of the first experiment. Since, at the current stage of the study, it is necessary to determine the possibility of form recognition to train and test the software performance, photographs obtained in the Power Sieve3 (PS3) automatic particle size distribution system (size of rock pieces) are used for form recognition. Figure 15 shows the stages of fragmentation recognition in Power Sieve3 (PS3). The fragment form recognition system presents a fairly good result. The form recognition error does not exceed 20 percent in comparison with the experimental data, carried out in manual mode by a piece-by-piece measurement of each piece and sieve analysis. However, it must be emphasized that this system has been tested only on the available  
Figure 8.0 Software interface for defining the fragment form distribution. Figure 8.1 Stages of rock fragmentation recognition in the Power Sieve3 software (PS3). photographs of experiments and has not been applied in industrial conditions. In present work, the system is presented as a demonstration of the possibility of creating such systems, and it certainly needs to be improved. Thus, the obtained conclusions described in the article should be additionally confirmed by a larger series of experiments, while the algorithm and the form recognition system should operate in a continuous mode. This will require the adaptation of the developed system to these conditions. This will be a continuation of the current research. Thus, the work presents one of the components presented in Figure 2, which is given additionally to explain the practical applicability of the obtained solutions. The main idea of the paper is the need to determine (control) the pieces' form at each stage of mining/processing of the minerals. This paper presents how this information can be obtained, i.e., the \"I\" component. During the experiment, the authors obtained this information \"manually\" by measuring each piece. It has been proposed that in industrial conditions, it is necessary to add a module for fragment form evaluation to the system that determines the grading (average piece size)--this option will not require large investments in hardware and software. For this purpose, the authors showed how a photo processed by the software to determine the average size of a lump can be refined to determine the form of lumps. Thus, the input information of the model is the images from this software, obtained at each process. In the present work, pieces of rock of various shapes and sizes were used as input information. The output information is the fragment form distribution. During the experiment, the analytical component of this figure is that the fragment form distribution was considered at four different stages. The result showed that optimization should be carried out by considering the form distribution at all stages. For example, when we analyze the distribution of the form at once on three technological stages, we can conclude that the more spilt form there is, the greater the yield of fines is. In fact, during blasting, the yield of fines was 10%, and after the third stage--30%. However, the natural structure, i.e., geological stage, shows that the spilt form is half of a cube plus a square in the aggregate and this fact requires analysis and verification with a larger volume of data.