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。