Christian Niemann-Delius

Production Scheduling of Open Pit Mines Using Particle Swarm Optimization Algorithm

Determining an optimum long term production schedule is an important part of the planning process of any open pit mine; however, the associated optimization problem is demanding and hard to deal with, as it involves large datasets and multiple hard and soft constraints which makes it a large combinatorial optimization problem. In this paper a procedure has been proposed to apply a relatively new and computationally less expensive metaheuristic technique known as particle swarm optimization (PSO) algorithm to this computationally challenging problem of the open pit mines. The performance of different variants of the PSO algorithm has been studied and the results are presented.

Proceedings of the 12th International Symposium Continuous Surface Mining : Aachen 2014

In open pit mines, one of the key aspects of automation is the transport of the mined minerals. Due to their economic benefit, conveyor belts are used to transport masses continuously. High availabilities and safe working conditions can be achieved by automating the process. Especially the feeding of the conveyor system has a strong automation potential. At the moment, the positioning of transfer booms or transfer chutes is done manually by a machine operator. The decisions of the operator are driven by his experience and his visual perception. The visual perception is often limited, e.g. by low light (in the evenings or at night), blinding by the sun or other environmental conditions such as dust or rain which can be present in open pit mining. This can lead to sub-optimal loading of the material. In case of off-centered loading, the conveyor belt can start to drift away from a centered position, which is called skewing. This skewing results in increased wear and tear of the system leading to breakdowns or increased maintenance times. Additionally, the transport capacity of the conveyor belt decreases because less area can be loaded with material. To detect skewing on conveyor belts, various systems are available on the market. The most common types of detection systems are mechanical components like switches and guide roller constructions. A second group of sensors used for skewing detection are supersonic systems. Both, mechanical and supersonic systems are not able to prevent belt skewing. These systems only detect an existing misalignment. To be able to prevent belt misalignments, a system based on long-wavelength infrared (LWIR) cameras which monitor the loading process as well as the position of the conveyor belt is proposed by the authors. The obtained data is correlated and analyzed with regard to the position of the belt when entering the loading station, the loading process itself and the belt position when leaving the station. This data can either be used for automation or if visualized to the operator, as an assistance system. This information can be used to optimize the loading process in order to prevent skewing, or to counteract already existing drift of the conveyor belt to prevent damages on the conveyor belt or other systems.

Research on Energy Consumption in Open Pits of the German Quarry Industry

Quarrying of natural stone is an energy-intensive process. The utilization of this type of raw materials will remain essential in the future. Thus, a systematic improvement of the energy efficiency in this mining branch will gain sustainable benefit.

Past, Present and Future of Metaheuristic Optimization Methods in Long-Term Production Planning of Open Pits

From a mathematical point of view, the problem of open pit production planning is a very large and complex challenge that cannot be solved by mathematical programming in an appropriate period of time. Clear definition of ore bodies normally requires that several millions of blocks be included in the block model, which makes the optimization problem almost impossible to be solved completely using traditional mathematic programming methods. Metaheuristic optimization algorithms are a new class of tools, which have shown a good potential in the solution of large, complex and poorly understood optimization problems. In this paper, after a brief review of the previously addressed metaheuristic optimization methods in literature, including Genetic Algorithm (GA) and Simulated Annealing (SA), the principles of a metaheuristic algorithm, newly developed at the Institute of Surface Mining and Drilling of RWTH Aachen University and based on Ant Colony Optimization (ACO), are explained. Finally, the applicability of other potential metaheuristics such as Particle Swarm Optimization, Tabu Search, Bee Colony Optimization etc. in the field of open pit mine planning is discussed.ZusammenfassungIm Sinn der Mathematik ist die Langfristplanung von Tagebauen eine sehr großes und komplexes Problem. Die Definition des bauwürdigen Bereichs erfordert normalerweise, dass mehrere Millionen Blöcke eines geologischen Block-Modells einbezogen werden müssen, wodurch das Optimierungsproblem fast unmöglich allein unter Verwendung traditioneller mathematischer Programmiermethoden vollständig gelöst werden kann. Metaheuristische Optimierungsalgorithmen sind eine neue Klasse von Werkzeugen, die ein großes Potenzial bei der Lösung von großen, komplexen und kaum verstanden Optimierungsprobleme gezeigt haben. Die vorliegende Abhandlung führt zunächst in die bisherige Literatur zu den Metaheuristischen Optimierungsmethoden wie Genetic Algorithm (GA) und Simulated Annealing (SA) ein. Es wird weiterhin das Prinzip einer neuen, am Institut für Rohstoffgewinnung über Tage und Bohrtechnik der RWTH Aachen University entwickelten und auf dem Ameisenalgorithmus (Ant Colony Optimization, ACO) basierenden Methode erläutert. Abschließend wird die Anwendbarkeit anderer Metaheuristiken wie Particle Swarm Optimization (PSO), Tabu Search, Bee Colony Optimization etc. im Bereich der Tagebauplanung diskutiert.

Betriebsmittel, Betriebstechnik und Betriebsorganisation im Tagebau

Betriebsmittel sind die Werkzeuge, mit denen der Tagebaubetrieb realisiert wird. Dazu gehoren die Anlagen und Gerate (Technik) fur die Haupt-, Neben- und Hilfsprozesse sowie die zu ihrem Betrieb notwendigen Hilfsstoffe.

A Differential Evolution based approach for the production scheduling of open pit mines with or without the condition of grade uncertainty

Abstract Production scheduling of open pit mines seeks to define such a temporal flow of ore and waste materials from a mine that maximizes a project’s Net Present value (NPV), while satisfying different physical and operational constraints. To achieve this objective, different mathematical formulations have been proposed in the technical literature. However, solving these formulations for a real sized open pit mine could be extremely difficult and computationally challenging job. In order to make this job computationally tractable, different heuristic and metaheuristic techniques are commonly used. This paper presents the results of a study where a real valued population based metaheuristic technique known as Differential Evolution (DE) algorithm has been used with the aim to solve the production scheduling problem of open pit mines with low to moderate computational cost with or without the condition of grade uncertainty. Three different case studies revealed the capabilities and efficiency of DE algorithm by producing sufficiently good solutions of the said with moderate computational cost.

Analysis-Specific Standardization of Quarries to Determine the Potential for the Application of Belt Conveyor Systems

With a yearly power consumption of about 1,700,000 MWh, the quarry industry appears to be one of the most energy-intensive sectors among German industries. In-pit transport operations require approx. 40% of the entire power demand, generating some 50% of the total mining costs. To date haulage is mostly done by mine trucks, driven by diesel engines with a total annual fuel consumption of 68 million liters, emitting an equivalent of 208,000 tons of carbon dioxide. Substitution of the mine trucks by establishing belt conveyors will on the one hand significantly reduce the emissions, and on the other increase energy efficiency in in-pit transportation. As every open pit requires a specific approach in order to find a suitable conveying system, a standardized analysis is not possible. In order to achieve a differentiated statement on the suitability of continuous conveyors according to various structural properties, a classification and standardization of quarries with similar transport parameters has been established. An individual scheduling of conveying and machine usage in the different types of quarries will allow a comparison of optimized constellations of the different haulage systems within the respective field of application, in order to quantify and compare ecological and economical aspects among the haulage systems.

Application of Nonlinear Interpolation Based Methods in Open Pit Mines Planning and Design

In this paper a new method of modeling variable slope angles has been presented based on the nonlinear interpolation method. Slope angle modeling and defining precedency of the blocks are the vital parts of almost any open pit optimization algorithm. Traditionally heuristic patterns such as 1:5 or 1:9 have been used to generate slope angles. Cone template based models were later employed in developing variable slope angles. They normally use a linear interpolation process for determination of slope angles between the given directions which leads to sharp and non-realistic pits. The other elliptical alternatives suffer from having limitations in defining slope angles in non-geographical directions. Current paper describes a new variable slope angles modeling method using the spline interpolation theory which is a variant of nonlinear interpolation methods. The method is capable to consider any number of slope angles in any desired direction as well as creating quite accurate and realistic pit shapes. Three major types of the spline interpolation including cubic, quadratic and cardinal are tested, however, the cubic form is preferred due to more realistic outcomes. Main steps of the method are described through a numerical case study.

Planung von Braunkohlentagebauen

Bergbauprojekte setzen wirtschaftlich gewinnbare Vorrate voraus und sind standortgebunden. Ihre Planung muss auser den Gegebenheiten der Lagerstatte auch alle weiteren Einflussfaktoren einbeziehen. Durch die bei Tagebauen auf flozartigen Lagerstatten sukzessiv fortschreitende Inanspruchnahme groser Flachen verstarkt sich die Anforderung an Umweltvertraglichkeit. In Folge der uberwiegend engen Koppelung der Braunkohlennutzung an die Stromerzeugung ubertragt sich die Standortbindung auch auf die Verwertungsanlagen, i.e. im Wesentlichen die braunkohlebefeuerten Kraftwerke.