Mahmut Yavuz

The application of the analytic hierarchy process (AHP) and Yager’s method in underground mining method selection problem

Underground mining method selection (UMMS) is one of the most important decisions in mining engineering. Choosing a suitable underground mining method to carry out extraction from a mineral deposit is very important for all stage of mining operations. In practice, UMMS is one of the multiple attribute decision-making (MADM) problems and mining engineers have some difficulties in making the right decision in the multiple criteria environment. In this paper, the following two similar MADM methods are described: analytic hierarchy process and fuzzy multiple attribute decision-making are applied to select the optimal underground mining method for lignite mine located in Istanbul. At the end of decision-making process, sensitivity analysis process is applied for each method.

A decision support system for underground mining method selection

Underground mining method selection (UMMS) is one of the most important decisions that should be made by mining engineers. Choosing a suitable underground mining method to carry out extraction from a mineral deposit is very important in terms of the economics, safety and the productivity of mining operations. In reality, UMMS is one of the Multiple Criteria Decision Making (MCDM) problems and decision makers have some difficulties in making the right decision in the multiple criteria environment. In this paper, a decision support system for underground mining method selection (UMMSDSS) has been designed and developed in order to take into account the whole related problem criteria, research the entire effects of different scenarios of all available criteria and carry out sensitive analysis when needed. UMMS-DSS was designed as to use Analytic Hierarchy Process (AHP), one of the MCDM methods, to manage those tasks and to produce acceptable solution alternatives.

Implementation and comparison of four stope boundary optimization algorithms in an existing underground mine

Abstract Deeper deposits become the future of mining as an increasing amount of shallow deposits are exploited. Consequently, the mining industry is being forced to extract minerals from deeper deposits using underground mining methods. This increased the demand for underground mine planning and optimization techniques. Stope boundary optimization is an important step of underground mine design and planning due to its direct impact on the economics of the project. It focuses on maximising the economic profit by selecting the best possible layout; by considering operational, geotechnical and physical constraints. There are a number of algorithms that have been developed for stope boundary optimization for the last two decades. In this paper, an existing underground mine is examined where sublevel stoping mining method is applied. Four algorithms are applied to this underground mine to investigate their applicability in underground mine planning and design process. The selected algorithms are Floating Stope, Maximum Value Neighbourhood, and two special applications which are developed by Sens and Topal and Sandanayake and Topal. The capabilities and limitations of these algorithms are evaluated and compared to each other. Then, they are compared with the stope optimization results from an existing underground mine.

Equipment Selection by using Fuzzy TOPSIS Method

In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

Plant Location Selection in Natural Stone Industry

Determining the most convenient plant location is one of the commonly encountered problems in engineering applications. This paper presents an Analytic Hierarchy Process (AHP) model, which is developed for selecting the optimum plant location for marble/travertine factories in natural stones processing industry. The whole criteria which affect the decision making process in marble industry were determined to solve plant location problem in the AHP model. To determine optimum marble plant location for a new marble factory, which is planned to install by a mining firm located in the Eskisehir region in Turkey, an analysis was carried out by introducing the AHP method which is one of the well-known classical Multiple Attribute Decision Making (MADM) methods. This analysis shows that the AHP method can successfully be applied for the selection of plant location as well as any decision making process in natural stone industry.