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Sustainable Development (SD) has played an important role in all industries and mining activities. The Internet of Things (IoT), interacting with industrial machines or home appliances through an interconnected network, can assist in developing real-time platforms for monitoring and operating a complex production system with minimal intervention of humans, which made it possible to benefit from the data obtained to increase production rate, Net Present Value optimization, workforce and machine safety, and decreasing pollution. Ideal automated mining can be achieved by designing an IoT based framework and suitable SD assessment. This research aims to achieve a holistic understanding of the current IoT scenario by conducting a comparative analysis of the prevailing literature regarding IoT applications in the mining and SD area. The results showed that, in the economic index of sustainability, mining activity based on IoT can increase productivity, wealth, income, and GDP and decrease operating expenses, depreciation costs, and total cost. From environmental point of view, a significant reduction in emission and pollution can be obtained. Also, the increase in workforce safety and positive impact on culture and knowledge are the components of the social index of sustainability. These activities are followed by some significant challenges such as developing infrastructures, modern machinery, adequate security for data transmission, increase business in the area, creating new jobs for individuals, especially those who have lost their jobs. It's essential to devise new rules to protect local people, properly distribute the wealth gained from this development to improve the infrastructure of the mining area. [ABSTRACT FROM AUTHOR]

The potential of occurrence of coal self-heating is controlled by various properties, both intrinsic and extrinsic. In the intrinsic properties, the maceral content has an important role in influencing its occurrence. This parameter has not been discussed in a comprehensive study among the researchers. Thus, the study of the influence of this parameter on coal self-heating is required. In the present work, the coal self-heating potential was predicted based on the maceral content. A total of 51 coal samples from different underground coal fields in Iran with different percentages of maceral content were collected, and R70 test method was carried out on each coal sample. Then, the regression analysis technique was used for modeling and predicting the coal self-heating potential. For validation and testing, 11 coal samples were randomly gathered from coalfields, and R70 test method was carried on each coal sample and results obtained were compared through a regression analysis. By examining and comparing the results and values obtained from R70 test method and the regression analysis, it was found that increase in the vitrinite and liptinite contents and decrease in the inertinite content increased the coal self-heating potential. [ABSTRACT FROM AUTHOR]

Among the fossil fuels, coal is the most widely used one all over the world for different purposes and is a stable source of energy. Coal mining has serious hazards such as spontaneous combustion. Many factors can influence the tendency for occurrence of this phenomenon in coal mines and coal storages, one of which is the petrographic characteristics (maceral and pyrite contents). The petrographic characteristics are directly affected by the growth of coalification and origin of coal forming. In this research work, firstly, the maceral and pyrite contents in coal samples were identified in two various mines in Iran (Tabas Parvadeh and Eastern Alborz coal mines). Then the spontaneous coal combustion propensity of each sample was measured using the Crossing Point Temperature (CPT) test method. The aim for carrying out this research work was to measure the effect of the maceral and pyrite contents on the grade of spontaneous coal combustion propensity. It was found that the pyrite contents and the vitrinite, liptinite, and inertinite mean levels in the Tabas Parvadeh and Eastern Alborz coal mines were (2.08%, 53.30%, 9.91%, 34.71%) and (1.14%, 53.06%, 6.39%, 39.41%), respectively. The mean CPT value was 148.43ºC in the Tabas Parvadeh coal mines and 175.86ºC in the Eastern Alborz coal mines. By examining the results of the experiments and comparing the CPT values, it was found that with an increase in the liptinite and pyrite contents and a decrease in the inertinite content, the Tabas Parvadeh coal mines tend to have more tendency for spontaneous coal combustion in comparison with the Eastern Alborz coal mines. [ABSTRACT FROM AUTHOR]

Maintenance cost is a significant part of production costs. Hence, logistics and spare part management should be considered early in the design and operational phase. The reliability characteristic of the item can be used effectively to spare part prediction (SPP). In mining industries, the reliability characteristic can be affected significantly by the operational conditions. In this study, to have an accurate SPP, covariate-based reliability models have been used to estimate the required number of tire spare parts for a dump truck fleet. The outputs represent a significant difference in the required spare parts' management, when considering and ignoring covariates. [ABSTRACT FROM AUTHOR]

Most of the mine design methods, especially in underground mining depend on the rock mechanics and thus, they are based on rock behavioral systems. Existence of uncertainty in the rock physical and mechanical parameters leads this assessment to be impossible. In such situation, the system thinking methods can be useful. The aim of this paper is to apply system thinking-based techniques for assessment of the rock mass cavability in block caving mines. For this purpose, fuzzy rock engineering system (FRES) and the decision-making trial and evaluation laboratory (FDEMATEL) methods are used to investigate caving behavioral system. The interrelationships and structure of the parameters involved in the rock mass cavability were determined by these methods. In addition, the parameters were categorized from causality point of view and ranked due to their importance. Finally, two methods were compared in the studying a complex system like the cavability of rock masses from their advantages and disadvantages point of view. This study shows that such analysis is useful in practice to better understanding rock behavior and its impact on the working space regard to the safety and the productivity. [ABSTRACT FROM AUTHOR]

This paper proposes a cascade high-gain observer for a class of triangular nonlinear systems with large and diverse time delays at states and output equation. Compared with some existing results in the literature, the main contribution is to consider the simultaneous and diverse delays in both states and output and further, to propose a cascade observer in dealing with arbitrarily large delayed measurements. By choosing a suitable Lyapunov-Krasovskii functional, the sufficient condition is presented that guarantees the exponential convergence of observation error to the origin. Simulation results on a numerical example and a practical case study involving inverted pendulum are finally given to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Once the performance characteristics of a system have been determined, engineers are often faced with the task of identifying the critical components. The objective of this identification is to prioritise improvements in the systems and the efforts to bring these about in the areas that will have the most effect on the system's performance. Availability is an important metric, used to assess the performance of complex systems. Having the availability importance measure (AIM), which determines the importance of items regarding the availability of the system, can help designers and managers to improve performance and minimise the life cost of the system. This paper has developed an AIM for complex systems. Thereafter, the application of the developed importance measure is illustrated by a case study. [ABSTRACT FROM AUTHOR]

In this article, the reliability of the cable system of a drum shearer machine was studied and analysed using operation and maintenance data from an Iranian mine for a period of two years. The tests for trend and serial correlation show that the times between successive failures for the cable system are not independent and identically distributed. A goodness-of-fit test shows that the power law process model provides a good fit to the failure data of this system. After parameter estimation for the power law model, reliability and failure rate plots were obtained. Based on analysis and results, a period of 125 h was defined as the reliability-based maintenance interval for the cable system of the shearer. The analysis shows that, by using this strategy, the reliability of the system will improve by at least 50%. [ABSTRACT FROM AUTHOR]

In this article, an improved method for eigenvalue assignment via state feedback in the linear time-invariant multivariable systems is proposed. This method is based on elementary similarity operations, and involves mainly utilisation of vector companion forms, and thus is very simple and easy to implement on a digital computer. In addition to the controllable systems, the proposed method can be applied for the stabilisable ones and also systems with linearly dependent inputs. Moreover, two types of state-feedback gain matrices can be achieved by this method: (1) the numerical one, which is unique, and (2) the parametric one, in which its parameters are determined in order to achieve a gain matrix with minimum Frobenius norm. The numerical examples are presented to demonstrate the advantages of the proposed method. [ABSTRACT FROM AUTHOR]