An expert system for underground coal mine planning
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AGH University of Science and Technology, Krakow, Poland
Gospodarka Surowcami Mineralnymi – Mineral Resources Management 2017;33(2):113-127
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ABSTRACT
In the current market situation, mining companies are faced with the necessity to take actions to improve the efficiency of the mining process. Some of these actions enforce a centralization of activities in the field of deposit economy and planning of mining operations in these companies. In the planning process with such scope the large knowledge of designers is required, which could be additionally supported by a knowledge base, supplied by information and data obtained during the completion of mining works, which also allows for use of the expert knowledge of other organizational units of the mine or the company. The paper presents an original expert system for mining works planning in the underground hard coal mines (MinePlanEx). The aim of the developed system is to support the designers of production planning in hard coal mines within the scope of: equipment selection, mining machinery combining into equipment sets and determining characteristic curves regarding the production results in the planned excavations. Knowledge of the system is represented by the rules selected with the chosen data mining techniques (association rules and classification trees) and obtained from experts. The first part of the paper presents a knowledge base, knowledge acquisition module and inference module which are the main components of the system. The second part contains an example of system operation.
METADATA IN OTHER LANGUAGES:
Polish
System ekspertowy dla potrzeb planowania robót górniczych w podziemnych kopalniach węgla kamiennego
system ekspertowy, górnictwo węgla kamiennego, planowanie robót górniczych, zarządzanie wiedzą
W obecnej sytuacji rynkowej przedsiębiorstwa górnicze stają przed koniecznością podjęcia działań, mających na celu zwiększenie efektywności prowadzonego procesu wydobywczego. Wśród tych działań znajdują się również łączenia kopalń (lub ich części), które wymuszają pewną centralizację działań w zakresie gospodarki złożem i planowania robót górniczych w tych przedsiębiorstwach. Dla poprawnej realizacji procesu planowania w takim zakresie wymagane jest posiadanie odpowiedniego zasobu wiedzy członków zespołu projektującego, który powinna uzupełniać baza wiedzy, zasilana informacjami i danymi uzyskanymi w miarę realizacji zaprojektowanych robót przygotowawczych i eksploatacyjnych oraz umożliwiająca wykorzystanie wiedzy ekspertów z innych jednostek organizacyjnych kopalni lub przedsiębiorstwa. W artykule zaprezentowano oryginalny system ekspercki do planowania robót górniczych w podziemnych kopalniach węgla kamiennego (MinePlanEx). Celem systemu jest wspieranie projektantów planowania produkcji w kopalniach węgla kamiennego w zakresie doboru sprzętu do warunków geologiczno-górniczych i określania charakterystyk dotyczących wyników produkcyjnych w planowanych wyrobiskach. Wiedza w systemie reprezentowana jest przez reguły wyznaczone z wykorzystaniem wybranych technik drążenia danych (reguły asocjacyjne oraz drzewa klasyfikacyjne) oraz uzyskane od ekspertów. W pierwszej części artykułu przedstawiono bazę wiedzy, moduł akwizycji wiedzy i wnioskowania, które są głównymi składnikami systemu. Druga część zawiera przykład działania systemu.
REFERENCES (27)
1.
Basu, A.J., and Lineberry, G.T. 1995. Selection of mobile equipment for underground coal mining: an expert system approach. Mineral Resources Engineering 71, pp. 71–88.
2.
Basu, A.J., Yuejin, L., and Singh, R.N. 1991. An overview of condition monitoring and an expert system for longwall mining machinery. Mining Science and Technology, 13, 3, pp. 279–290.
3.
Britton, S.G. 1987. Computer-based expert system aids underground mine planning. Coal Age, 92, 1, pp. 21–24.
4.
Brzychczy et al. 2011 – Brzychczy, E., Magda, R., Franik, T., Kęsek, M., Woźny, T. and Napieraj, A. 2011. An expert system for supporting mine production planning in multi-plant mining enterprises [In:] S. Eskikaya ed., 22nd World Mining Congress, Volume II , Istanbul, pp. 551–558.
5.
Brzychczy et al. 2013 – Brzychczy, E., Magda, R., Franik, T., Kęsek, M., Napieraj, A., and Woźny, T. 2013. Principles of the advisory system supporting planning of first workings and exploitation works in hard coal mines. AGH University of Science and Technology Press, Cracow (in Polish).
6.
Golak, S. and Wieczorek, T. 2014. Concept of expert system for evaluation and improvement of eco-efficiency of mines. Studia Informatica, 35, 2, pp. 213–222.
7.
Grayson et al. 1990 – Grayson, R.L., Watts, C.M., Singh, H., Yuan, S., Dean, J.M., Reddy, N.P., and Nutter, R.S., Jr. 1990. A knowledge-based expert system for managing underground coal mines in the US. IEEE Transactions on Industry Applications, 26, 4, pp. 598–604.
8.
Grychowski, T. 2014. Multi sensor fire hazard monitoring in underground coal mine based on fuzzy inference system. Journal of Intelligent and Fuzzy Systems Vol. 26, No. 1, pp. 345–351.
9.
Hart, E., and Duda, R. O. 1977. PROSPECTOR – A Computer-Based Consultation. System for Mineral Exploration. California Menlo Park: SRI International, Artificial Intelligence Center.
10.
Hosack et al. 2012 – Hosack, B., Hall, D., Paradice, D. and Courtney, J.F. 2012. A Look toward the Future: Decision Support Systems Research Is Alive and Well. Journal of the Association for Information Systems Vol. 13, Special Issue, May, pp. 315–340.
11.
Kozan, E. and Liu, S.Q. 2012. A demand-responsive decision support system for coal transportation. Decision Support Systems, 54, pp. 665–680.
12.
Kozielski et al. 2015 – Kozielski, M., Sikora, M. and Wróbel, Ł. 2015. DISESOR – decision support system for mining industry. Proceedings of the Federated Conference on Computer Science and Information Systems. ACSIS , Vol. 5, Łódź, pp. 67–74.
13.
Liebowitz, J. ed. 1997. The handbook of applied expert systems. CRC Press.
14.
Liu, X. and Huang, X. 2008. Research on Pre-warning Expert System of Coal Mine Gas Safety Based on Object-oriented. Knowledge Acquisition and Modeling Workshop. IEEE International Symposium, pp. 1109–1112.
15.
Liu et al. 2010 – Liu, Z., Zeng, Q., Wang, Ch., and Zhao, Y. 2010. Research on ontology-based knowledge representation and retrieval of coal mining equipment selection and matching expert system. International Conference on Intelligent Control and Information Processing (ICICIP), Dalian, pp. 776–779.
16.
Miah et al. 2014 – Miah, S., Kerr, D. and von Hellens, L. 2014. A Collective Artefact Design of Decision Support Systems: Design Science Research Perspective. Information Technology & People, Vol. 27 Issue 3, pp. 259–279.
17.
Nageshwaraniyer et al. 2012 – Nageshwaraniyer, S.S., Meng, C., Maghsoudi, A., Son, Y. and Dessureault, S. 2012. Simulation-based Decision Support System for Sustainable Coalmining Operations. IIE Annual Conference. Proceedings, pp. 1–10.
18.
Paré et al. 2015 – Paré, G., Trudel, M.-C., Jaana, M. and Kitsiou, S. 2015. Synthesizing Information Systems Knowledge: A Typology of Literature Reviews. Information & Management Vol. 52, pp. 183–199.
19.
Perkin et al. 1986 – Perkin, R.M.G, Pitt, M. and Price, A. E. 1986. Expert systems: Practical Applications in a Traditional Industry, in Research and Development in Expert Systems III . Proceedings of Expert Systems‘86, Cambridge: University Press.
20.
Plümer, L. 1992. Expert systems in mining. Logic Programming in Action. Lecture Notes in Computer Science. Berlin/Heidelberg: Springer, pp. 118–126.
21.
Przystałka et al. 2016 – Przystałka, P., Moczulski, W., Timofiejczuk, A., Kalisch, M. and Sikora, M. 2016. Development of expert system shell for coal mining industry [In:] F. Chaari et al. (Eds.), Advances in condition monitoring of machinery in non-stationary operations. Proceedings of the Fourth International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO ’2014, Lyon, France, Springer International Publishing, Switzerland, pp. 335–348.
22.
Samanta, B.K., and Samaddar, A.B. 2002. Formulation of coal mining projects by expert system. Journal of Mines, Metals and Fuels, 50, 6, pp. 202–210.
23.
Stefaniak et al. 2014 – Stefaniak, P.K., Zimroz, R., Bartelmus, W. and Hardygóra, M. 2014. Computerised Decision-Making Support System Based on Data Fusion for Machinery System’s Management and Maintenance. Applied Mechanics and Materials Vol. 683, pp. 108–113.
24.
Streichfuss, M. and Burgwinkel P. 1995. An expert-system-based machine monitoring and maintenance management system, Control Engineering Practice, 3, 7, pp. 1023–1027.
25.
Webb, A. 1999. Statistical Pattern Recognition. New York: Oxford University Press.
26.
Yingxu, Q. and Hongguo, Y. 2010. Design and application of expert system for coal mine safety. Geoscience and Remote Sensing. Second IITA International Conference 1, pp. 452–454.
27.
Zhang, H. and Zhao, G. 1999. CM EOC – An expert system in the coal mining industry. Expert Systems with Applications, 16, 1, pp. 73–77.