Mohammad Javad Rahimdel1, Mohammad Karamoozian2 Abstract: Selection of the crusher required a great deal of design regarding to the mine planning。 Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making (MCDM) problem。 The present work explores the use of technique for order performance by similarity to ideal solution (TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran。 Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives。 Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem。 To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS)。 Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine。 79857
Key words: primary crusher; multi-criterion decision making (MCDM); technique for order performance by similarity to ideal solution; fuzzy set theory; Golegohar Iron Mine; gyratory crusher
1 Introduction
The mining equipment selection is the most importance aspect of mine production management。 Up to now, the empirical methods and engineering judgments have been widely used to the selection of the best primary crushers in open pit mining。 The present work explores new approach based on technique for order performance by similarity to ideal solution (TOPSIS) with fuzzy set theory to select the best primary crusher for Golegohar Iron Mine in Iran。 TOPSIS method was firstly proposed by HWANG and YOON [1] for solving multiple criteria decision problems。 According to this technique, the best alternative would be the one that is nearest to the positive ideal solution and farthest from the negative ideal solution [2]。 The positive ideal solution is a solution that maximizes the benefit criteria and minimizes the cost criteria, whereas the negative ideal solution maximizes the cost criteria and minimizes the benefit criteria [3]。 This method under fuzzy environment has been used for a variety of specific applications in decision making problem [4−14]。 However, its application in primary crusher selection has not been reported yet。 In this work, the extended TOPSIS method isconsidered which was originally proposed by CHEN [15]。 In classical TOPSIS, the ratings and the weights of the criteria are known precisely。 However, under many conditions, crisp data are inadequate to model real life situations since human judgments are often vague while decision makers cannot estimate their preferences with an exact numerical value [16]。 To assess the importance of the criteria and to evaluate the each alternative, the linguistic variables are used。 These linguistic variables are converted into triangular fuzzy numbers then fuzzy decision matrix is formed。 The closeness coefficient of each alternative is calculated after formation of weighted normalized fuzzy。 Regarding to these calculations, determination of the order of the alternatives and selection of the best one are possible。 模糊TOPSIS方法对初级破碎机英文文献和中文翻译:http://www.youerw.com/fanyi/lunwen_92562.html