E. Brzychczy

A Modern Tool for Modelling and Optimisation of Production in Underground Coal Mine

A new calculation tool allowing the user to model and optimise production in underground coal mines is presented in the paper. Hard coal plays an essential role in the world economics. Its consumption in 2011 increased faster than for any other energy produced from raw materials excluding renewable sources. Achieving the planned output levels depends, first of all, on results acquired in the mining design process. It is now possible to support this design process with modern tools, which can significantly increase future mine efficiency as well as the quality of the raw material extracted. The calculation service for optimisation of the production in underground coal mines OPTiCoalMine is one of such tools.

Artificial Immune Systems for Data Classification in Planetary Gearboxes Condition Monitoring

In the paper a problem of diagnostic data classification is discussed. The classic condition monitoring approach requires two examples of machines: one in a good and one in a bad condition. From the industrial perspective such a requirement is often very difficult to fulfill, especially in the case of machines with an unique design. To overcome it, we proposed to use the Artificial Immune System (AIS) based approach to classify multidimensional diagnostic data. AIS allows to recognize a change of the machine condition based on a training phase using the dataset related to a good condition. To validate the proposed procedure and assess efficiency of the condition recognition, an extra data set from another machine (of the same type) in a bad condition was used. In the paper several key issues related to the selection of parameters have been discussed.

Probabilistic Modeling of Mining Production in an Underground Coal Mine

The article presents probabilistic modeling of mining production in hard coal mines with the application of stochastic networks. The paper includes basic definitions and assumptions of the evolved method and the systematic enabling the description of network activities. As a results of calculations according to the mathematical model the paper presents probability distributions of output for each production flow and for a whole mine in each of the calculated variants. To estimate the risk of output results the standard deviation of the distribution was assumed. Probability distributions form the basis of the optimization procedure. An application of the developed method in a coal mine is presented.

Process-Oriented Approach for Analysis of Sensor Data from Longwall Monitoring System

In the paper we address possibility of industrial process analysis based on sensor data with the use of process-oriented analytic techniques. We propose in this area usage of process mining techniques. Important issue in the context of usefulness of industrial sensor data gathered in the monitoring systems for process analysis is proper level of abstraction of an event log.

Modelling of Processes with Use of Process Mining Techniques

The main purpose of the paper is presentation of new opportunities 7 for process modelling. In the literature review section, Petri nets as one of the 8 formal modelling notation of processes is highlighted and introduction of 9 relatively young research discipline – process mining – is presented. One of the 10 process mining tasks is process model discovery from event logs gathered in 11 informatics systems in enterprise. In the article practical example of process 12 model discovery with ProM software is given with use of real event log from 13 Volvo IT Belgium. In conclusions further opportunities of process mining 14 techniques in process management are emphasized. 15

Practical Aspects of Event Logs Creation for Industrial Process Modelling

Abstract In the paper we address the challenge of applying process mining techniques for discovering models of underground mining operations based on a sensor data. The paper presents practical approach of creation an event log based on industrial sensors data gathered in an underground mine monitoring systems. The proposed approach enables to generate event logs at different generalization levels based on several numbers of discovered stages of devices performance. For discovering process stages data mining techniques such as exploratory data analysis, clustering and classification have been applied. Created event log has been used in one of the process mining tasks - process model discovery.

Evolutionary optimisation of coal production in underground mines

In the paper optimisation of coal production in multi-plant company 7 is described. Optimisation problem and proposal of optimisation criterion were 8 formulated. As modern solution in this area the developed evolutionary algorithm 9 is presented. An example of calculation results is presented. 10