The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

Stochastic-optimization of equipment productivity in multi-seam formations

Short and long range planning and execution for multi-seam coal formations (MSFs) are challenging with complex extraction mechanisms. Stripping equipment selection and scheduling are functions of the physical dynamics of the mine and the operational mechanisms of its components, thus its productivity is dependent on these parameters. Previous research studies did not incorporate quantitative relationships between equipment productivities and extraction dynamics in MSFs. The intrinsic variability of excavation and spoiling dynamics must also form part of existing models. This research formulates quantitative relationships of equipment productivities using Branch-and-Bound algorithms and Lagrange Parameterization approaches. The stochastic processes are resolved via Monte Carlo/Latin Hypercube simulation techniques within @RISK framework. The model was presented with a bituminous coal mining case in the Appalachian field. The simulated results showed a 3.51% improvement in mining cost and 0.19% increment in net present value. A 76.95yd³ drop in productivity per unit change in cycle time was recorded for sub-optimal equipment schedules. The geologic variability and equipment operational parameters restricted any possible change in the cost function. A 50.3% chance of the mining cost increasing above its current value was driven by the volume of material re-handled with 0.52 regression coefficient. The study advances the optimization process in mine planning and scheduling algorithms, to efficiently capture future uncertainties surrounding multivariate random functions. The main novelty includes the application of stochastic-optimization procedures to improve equipment productivity in MSFs --Abstract, page iii

Applications of simulation and optimization techniques in optimizing room and pillar mining systems

The goal of this research was to apply simulation and optimization techniques in solving mine design and production sequencing problems in room and pillar mines (R&P). The specific objectives were to: (1) apply Discrete Event Simulation (DES) to determine the optimal width of coal R&P panels under specific mining conditions; (2) investigate if the shuttle car fleet size used to mine a particular panel width is optimal in different segments of the panel; (3) test the hypothesis that binary integer linear programming (BILP) can be used to account for mining risk in R&P long range mine production sequencing; and (4) test the hypothesis that heuristic pre-processing can be used to increase the computational efficiency of branch and cut solutions to the BILP problem of R&P mine sequencing. A DES model of an existing R&P mine was built, that is capable of evaluating the effect of variable panel width on the unit cost and productivity of the mining system. For the system and operating conditions evaluated, the result showed that a 17-entry panel is optimal. The result also showed that, for the 17-entry panel studied, four shuttle cars per continuous miner is optimal for 80% of the defined mining segments with three shuttle cars optimal for the other 20%. The research successfully incorporated risk management into the R&P production sequencing problem, modeling the problem as BILP with block aggregation to minimize computational complexity. Three pre-processing algorithms based on generating problem-specific cutting planes were developed and used to investigate whether heuristic pre-processing can increase computational efficiency. Although, in some instances, the implemented pre-processing algorithms improved computational efficiency, the overall computational times were higher due to the high cost of generating the cutting planes --Abstract, page iii

Simulation of product transportation in open pit mines

A research report submitted to the Faculty of Engineering and Built Environment, University of Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Masters of Science in Engineering Johannesburg, 2015Open pit mines account for more than 60 percent of all surface mines, and haulage costs account for almost 60 percent of total operating costs for these mines. It necessitates maintaining an efficient haulage system where all fleet equipment performs effectively to achieve the mine’s objectives. Discrete event simulation supported by animation offers a powerful method for evaluating such systems. This research has developed a simulation software program using Visual Basic for Application (VBA), GPSS/H (General Purpose Simulation System), and PROOF 5 animation. Remaining within the defined assumptions and boundary conditions, the research combines the powers of three software languages to build a general-purpose, data-driven, and user-friendly simulation program. The research focuses on the study and simulation of some of the important complexities of the truck haulage system. These include uncertainty or system randomness, fleet heterogeneity, multi-loader multi-dump sites, bunching of haulers, and hauler dispatching. In the developed simulation program, the user is required to provide the inputs in the user-friendly environment of VBA. The simulation program arranges the inputs in a pre-arranged format and then sends them to GPSS/H. The simulation language generates a discrete event simulation model based on the receiving structural and operational data. After simulating the system, the model generates the simulation outputs and animation commands in separate files. VBA displays a summary of the simulation results, and PROOF 5 demonstrates the results in a 2-dimensional graphical animation along with detailed information. This research also includes three case studies based on hypothetical mines for the analysis of simulation results. It establishes comparisons between the dispatching policies of fixed allocation and variable allocation of Minimize Production Requirements (MPR), and shows that the MPR policy is more suitable to achieve the quality control objectives. The developed simulation program contributes by demonstrating the powers of simulation to analyse open pit haulage systems. It also shows how simulation can be utilized as a useful technique to answer many ‘what-if?’ questions and scenarios

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Assessment of the Hunter Valley Coal Export Supply Chain

We develop a decision support tool that assesses the throughput of a coal export supply chain for a given level of demand. The tool can be used to rapidly evaluate a number of infrastructures for several future demand scenarios in order to identify a few that should be investigated more thoroughly using a detailed simulation model. To make the natural model computationally tractable, we exploit problem structure to reduce the model size, and we employ aggregation as well as disaggregation to strengthen the structure of model. We use the tool in a computational study in which we analyze system performance for different levels of demand to identify potential bottlenecks

Manual Handling Problem Identification in Mining Industry: An Ergonomic Perspective

AbstractErgonomics processes described in the literature have been associated mostly with manufacturing, financial, elec-tronics, and office settings where working conditions tend to be rather constant and repetitive. The information presented in this paper demonstrates, however, that an ergonomics process can also be implemented in a setting such as mining where working conditions frequently change and workers are periodically exposed to extreme conditions. This paper describes how to identify manual handling problem in one of Indonesian Coal Company at South Kalimantan Mine in 2015. The process of problem identification and the impacts of the process on working conditions at the mine using Job Discomfort Survey, Manual Handling Checklist and Sample Decisison Matrix (DM) are reviewed. Barriers overcome and lessons learned are also described. Quotes from Coal Company em-ployees are included in the document to add an ergonomic perspective. Other industries with working conditions similar to mining, such as construction and retail, may find this information useful. The uniqueness of decision matrix is that DM is the research instrument that collect baseline data from supervisor interviews, Nordic-questionnaire, incident data and management concerns becomes task analysis which consist of observations, video taping, discomfort intervention, task measurements which end up with identify risk factors. Scope of coal mining in this paper is crushing & sizing and barge loading, as we know that the overall scope of coal mining are: overburden stripping, coal mining, loading coal from rom stockpile to coal hauler, coal hauling, haul road, crushing & sizing, barge loading, coal barging, floating cranes, coal terminal. Finally, the contribution is to help, prevent or reduce the occurrence of lifting-related lower-back injurie

Proceedings of the 2004 Coal Operators\u27 Conference

Proceedings of the 2004 Coal Operators\u27 Conference. All papers in these proceedings are peer reviewed in accordance with The AUSIMM publication standard

Оптимизация устойчивости функционирования подсистем очистного забоя

Предложен новый подход к оценке устойчивости функционирования производственных подсистем в очистном забое угольных шахт. Для решения задачи применен комплексный подход, основанный на внедрении модели устойчивости производственных связей в очистном забое, а также критериев принятия решений в условиях неопределенности для разработки рекомендаций по повышению технико-экономических показателей. Установлено, что устойчивость функционирования подсистем в очистном забое определяется соотношением потоков входящих ресурсов в виде подготовленного фронта очистных работ, средств механизации, технологических параметров и выходных – в виде конечного уровня производительности, себестоимости добычи и др. Особое внимание уделено разработке программного обеспечения для внедрения описанных подходов в производство

Contribution to the capacity determination of semi-mobile in-pit crushing and conveying systems

As ore grades decline, waste rock to ore ratios increase and mines become progressively deeper mining operations face challenges in more complex scenarios. Today´s predominant means of material transport in hard-rock surface mines are conventional mining trucks however despite rationalisation efforts material transportation cost increased significantly over the last decades and currently reach up to 60% of overall mining. Thus, considerations and efforts to reduce overall mining costs, promise highest success when focusing on the development of more economic material transport methods. Semi-mobile in-pit crusher and conveyor (SMIPCC) systems represent a viable, safer and less fossil fuel dependent alternative however its viability is still highly argued as inadequate methods for the long term projection of system capacity leads to high uncertainty and consequently higher risk. Therefore, the objective of this thesis is to develop a structured method for the determination of In-pit crusher and conveyor SMIPCC system that incorporates the random behaviour of system elements and their interaction. The method is based on a structured time usage model specific to SMIPCC system supported by a stochastic simulation. The developed method is used in a case study based on a hypothetical mine environment to analyse the system behaviour with regards to time usage model component, system capacity, and cost as a function of truck quantity and stockpile capacity. Furthermore, a comparison between a conventional truck & shovel system and SMIPCC system is provided. Results show that the capacity of a SMIPCC system reaches an optimum in terms of cost per tonne, which is 24% (22 cents per tonne) lower than a truck and shovel system. In addition, the developed method is found to be effective in providing a significantly higher level of information, which can be used in the mining industry to accurately project the economic viability of implementing a SMIPCC system