Logistic evaluation of an underground mine using simulation

Fioroni, Marcelo Moretti; Santos, None Leticia Cristina Alves dos; Franzese, Luiz Augusto G.; Seixas, Josiane Cordeiro; Penna, Bruno; Alkmim, Gerson Mendes de

doi:10.1590/0370-44672014670181

Cited by 9 publications

(8 citation statements)

References 2 publications

(2 reference statements)

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“…In recent years, a variety of simulation techniques have been actively developed to simulate underground mine truck haulage systems to design optimized production tasks and establish usage plans for haulage equipment [38,39]. The truck haulage simulations provide a variety of functions such as selecting optimal equipment combinations [40][41][42][43][44][45][46], establishing equipment dispatch plans [47][48][49], and analyzing optimal haulage paths. Normally, trucks' travel time measurement data are used as the input data in truck haulage simulations.…”

Section: Utilization Of Mine Big Data For Efficient Mine Operationmentioning

confidence: 99%

Simulation of Truck Haulage Operations in an Underground Mine Using Big Data from an ICT-Based Mine Safety Management System

Baek

Choi

2019

Applied Sciences

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Information communication technology (ICT)-based mine safety management systems are being introduced at numerous mining sites to track the location of equipment and workers in real time and monitor environmental changes. This paper presents the results of a case study in which the big data created by an ICT-based mine safety management system are used for simulating truck haulage operations. An underground limestone mine located in Danyang, South Korea was studied, and the data generated over three months, from October 1 to December 31, 2018, were analyzed. Truck tag packet data recognized by relays were extracted and analyzed to calculate the averages and standard deviations of the truck travel times of each mine segment. A discrete event simulation program that simulates truck haulage operations in the study area was developed. Haulage times, the number of haulage operations, production output, and truck delay times were predicted, and results were compared with the actual operation results that were obtained on January 2 and 9, 2019. The difference between the predicted and actual results for the total amount of loaded ore was 30 tons for January 2 and 0 tons for January 9. The mean absolute error between the predicted and observed truck travel times was 0.13 min for January 2 and 0.14 min for January 9. The truck travel times that were measured differently according to the data aggregation period were set as temporal factors, and truck haulage simulations were performed. The results showed that more reliable simulation results were obtained as data accumulation time increased.

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Section: Utilization Of Mine Big Data For Efficient Mine Operationmentioning

confidence: 99%

Simulation of Truck Haulage Operations in an Underground Mine Using Big Data from an ICT-Based Mine Safety Management System

Baek

Choi

2019

Applied Sciences

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“…Because of the importance of these problems, there are a large number of papers on the use of simulation in the development and optimization of mining systems [2,3,4,5]. There are also a large number of simulation tools both universal simulation systems and specialized systems and packages for simulation of mining systems.…”

Section: Institute Of Computational Technologies Of Siberianmentioning

confidence: 99%

Using Simulation for Development of Process Control Systems in Mining

Okolnishnikov

Rudometov

Shakirov³

et al. 2017

Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

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Abstract-This paper describes our own visual interactive simulation system specialized in simulation of technological processes in mining. A new model of the crushing-grading mill was developed with the help of this simulation system. The model was integrated with a process control system of the crushing-grading mill. The model was used for debugging and testing of the process control system of the crushing-grading mill with the help of different "in-the-loop" ways.

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“…In the paper [16], there is the methodology of selecting the stoping equipment using graphs and network models, and in the paper [17], there is its practical use. It is worth noting that this approach was used to solve transportation issues [18], tasks for the resource allocation at the mine [19], as well as for ventilation of mine workings [20], as well as surface mining of mineral deposits [21,22].…”

Section: Introductionmentioning

confidence: 99%

Improving the process of coal extraction based on the parameter optimization of mining equipment

Hrinov

Khorolskyi

2018

E3S Web Conf.

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The aim of this paper is to develop and validate methods of choosing the means of the mining face mechanization. This paper analyses existing methods of optimizing processes in mining. It was established that the effectiveness of the performance map of coal field is formed by a group of technological, operational, and economic parameters which can be represented as a vector of solutions. To find the optimal solution, it was suggested to use network models and graphs. The essence of the technique is to represent the input and output (production level, prime cost) resource flows in an organized structure. Regularities of forming technological schemes of coalfield operation with a given level of performance, taking into account the relationship between technological parameters of mining face, operational parameters of the stoping equipment, technical and economic performance are defined. We developed the system for decision-making support, which allows optimizing operational parameters, reducing the production prime cost, and selecting the structure of the mechanized complex of stoping equipment with a specified level of performance. This paper describes approaches that can be used at the design stage of mining face and in the process of operation.

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Logistic evaluation of an underground mine using simulation

Cited by 9 publications

References 2 publications

Simulation of Truck Haulage Operations in an Underground Mine Using Big Data from an ICT-Based Mine Safety Management System

Simulation of Truck Haulage Operations in an Underground Mine Using Big Data from an ICT-Based Mine Safety Management System

Using Simulation for Development of Process Control Systems in Mining

Improving the process of coal extraction based on the parameter optimization of mining equipment

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