{"references": ["Hoseinie, S. H., Al-Chalabi, H., & Ghodrati, B. (2018). Comparison between simulation and analytical methods in reliability data analysis: A case study on face drilling rigs. Data, 3(2), 12.", "Liu, H., & Karen Yin, K. (2001). Analysis and interpretation of monitored rotary blasthole drill data. International Journal of Surface Mining, Reclamation and Environment, 15(3), 177-203.", "Stefaniak, P., Wodecki, J., Zimroz, R., \u015aliwi\u0144ski, P., & Andrzejewski, M. (2016). The multivariate analysis of monitoring system data from mining drilling machine. International Multidisciplinary Scientific GeoConference: SGEM, 2, 913-920.", "Wodecki, J., G\u00f3ralczyk, M., Krot, P., Zi\u0119tek, B., Szrek, J., Worsa-Kozak, M., ... & Czajkowski, A. (2020). Process Monitoring in Heavy Duty Drilling Rigs\u2014Data Acquisition System and Cycle Identification Algorithms. Energies, 13(24), 6748.", "Zi\u0119tek, B., Wodecki, J., Michalak, A., & \u015aliwi\u0144ski, P. (2021, November). Drill bit state-oriented drilling process classification with time-series data for wheeled drilling rigs. In IOP Conference Series: Earth and Environmental Science (Vol. 942, No. 1, p. 012010). IOP Publishing.", "G\u00f3ralczyk, M., Michalak, A., & \u015aliwi\u0144ski, P. (2021, November). Drill bit deterioration estimation with the Random Forest Regressor. In IOP Conference Series: Earth and Environmental Science (Vol. 942, No. 1, p. 012013). IOP Publishing.", "Thuro, K. (1997). Drillability prediction: geological influences in hard rock drill and blast tunnelling. Geologische Rundschau, 86(2), 426-438.", "Ghosh, R., Schunnesson, H., & Kumar, U. (2016). Evaluation of operating life length of rotary tricone bits using Measurement While Drilling data. International Journal of Rock Mechanics and Mining Sciences, 83, 41-48.", "Ataei, M., KaKaie, R., Ghavidel, M., & Saeidi, O. (2015). Drilling rate prediction of an open pit mine using the rock mass drillability index. International Journal of Rock Mechanics and Mining Sciences, 73, 130-138.", "Plinninger, R. J. (2008). Abrasiveness assessment for hard rock drilling. Geomechanik und Tunnelbau: Geomechanik und Tunnelbau, 1(1), 38-46.", "Isheyskiy, V., & Sanchidri\u00e1n, J. A. (2020). Prospects of applying MWD technology for quality management of drilling and blasting operations at mining enterprises. Minerals, 10(10), 925.", "Rai, P., Schunesson, H., Lindqvist, P. A., & Kumar, U. (2015). An overview on measurement-while-drilling technique and its scope in excavation industry. Journal of the Institution of Engineers (India): Series D, 96(1), 57-66.", "Ghosh, R., Gustafson, A., & Schunnesson, H. (2018). Development of a geological model for chargeability assessment of borehole using drill monitoring technique. International Journal of Rock Mechanics and Mining Sciences, 109, 9-18.", "Segui, J. B., & Higgins, M. (2002). Blast design using measurement while drilling parameters. Fragblast, 6(3-4), 287-299.", "Rai, P., Schunnesson, H., Lindqvist, P. A., & Kumar, U. (2016). Measurement-while-drilling technique and its scope in design and prediction of rock blasting. International Journal of Mining Science and Technology, 26(4), 711-719.", "Khorzoughi, M. B., & Hall, R. (2016). Processing of measurement while drilling data for rock mass characterization. International journal of mining science and technology, 26(6), 989-994.", "Vezhapparambu, V. S., Eidsvik, J., & Ellefmo, S. L. (2018). Rock classification using multivariate analysis of measurement while drilling data: Towards a better sampling strategy. Minerals, 8(9), 384."]}

In many underground mines the excavated ore is produced during the blasting process. Drilling machines that are used to drill the blastholes, where later the explosives will be mounted, are crucial for this task. In order to optimize the currently used techniques, great emphasis is placed on increasing the efficiency and safety of blasthole drilling operations. The natural consequence is the development of monitoring systems and algorithms for processing operational and historical data. In this article, we present the result of the analysis of drilling data carried out as part of the IlluMINEation project. The paper proposes an algorithm for work cycle detection for drilling machines, together with the estimation of general operating parameters and diagnosing the drilling process on the basis of long-term data. Based on the available data, selected components of the drilling cycles have been indicated. Several approaches based on the parameters of the defined cycles are proposed. These approaches can be used in the future to create a full-fledged system for examining the effectiveness and safety of mining drilling rigs.