A Multi Attribute Selection of Mobile Robot using AHP/M-GRA Technique

Today's highly competitive environment and volatile market conditions at national and international level are forcing the manufacturing concerns and its management to adopt the advance automated material handling equipment like mobile robots in a flexible manufacturing system FMS to meet the customers' demand regarding quality and variety of product at minimal cost. Selection of a robot is one of the most difficult problems in today's manufacturing environment. The problem has become more challenging due to increasing specifications and complexity of the robot. The main aim of this paper is to develop and implement an integrated methodology based on AHP Analytical Hierarchy Process and M-GRA Modified Grey Relational Analysis for the selection of a mobile robot for material handling in FMS environment. In this methodology, AHP technique has been used to assign the relative importance between mobile robot selection attributes and M-GRA technique is applied to determine mobile robot selection utility index. The proposed AHP/M-GRA technique is more suitable for the decision making in the presence of vagueness. The methodology is illustrated by means of an example. The ranking and evaluation of this process will provide a good guidance to the decision maker/user to select the appropriate material handling equipment on the basis of attributes. This is the novel effort in the area of robot selection.

[1]  Anjali Awasthi,et al.  An Analytical Hierarchical Process-based decision-making approach for selecting car-sharing stations in medium size agglomerations , 2008, Int. J. Inf. Decis. Sci..

[2]  Rosnah Mohd. Yusuff,et al.  Model development for post-implementation process of advanced manufacturing technology , 2013, Int. J. Inf. Decis. Sci..

[3]  Osman Kulak,et al.  A decision support system for fuzzy multi-attribute selection of material handling equipments , 2005, Expert Syst. Appl..

[4]  Luis G. Vargas,et al.  Inconsistency and rank preservation , 1984 .

[5]  T. Saaty.  Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network , 2004 .

[6]  Timothy J. Greene,et al.  A knowledge-based system for conveyor equipment selection , 2004, Expert Syst. Appl..

[7]  R. Venkata Rao,et al.  Multiple Attribute Decision Making in the Manufacturing Environment , 2013 .

[8]  Ravi Shankar,et al.  A review of some issues and identification of some barriers in the implementation of FMS , 2007 .

[9]  Iraj Mahdavi,et al.  Data envelopment analysis based comparison of two hybrid multi-criteria decision-making approaches for mobile phone selection: a case study in Iranian telecommunication environment , 2008, Int. J. Inf. Decis. Sci..

[10]  M. G. Bhatt,et al.  A multi-attribute selection of automated guided vehicle using the AHP/M-GRA technique , 2011 .

[11]  Hongyan Liu,et al.  The Relative Grey Relation Closeness Multicriteria Decision Making Method , 2006, Sixth International Conference on Intelligent Systems Design and Applications.

[12]  R. S. Lashkari,et al.  A multi-objective model of operation allocation and material handling system selection in FMS design , 2007 .

[13]  S. G. Deshmukh,et al.  Multi-attribute decision model using the analytic hierarchy process for the justification of manufacturing systems , 1992 .

[14]  Shankar Chakraborty,et al.  Design of a material handling equipment selection model using analytic hierarchy process , 2006 .

[15]  Edmundas Kazimieras Zavadskas,et al.  A New Logarithmic Normalization Method in Games Theory , 2008, Informatica.

[16]  Seyed Mohammad Asadzadeh,et al.  Evaluating of an AGV System in a CIM Unit: A Simulation Approach , 2007 .

[17]  T. Beckman,et al.  Business reengineering at a large government agency , 1997 .

[18]  Prasenjit Chatterjee,et al.  Selection of industrial robots using compromise ranking method , 2012 .

[19]  Rajesh Attri,et al.  Selection of cutting-fluids using a novel decision-making method: preference selection index method , 2014, Int. J. Inf. Decis. Sci..

[20]  Charles J. Malmborg,et al.  Analytical models for analysis of automated warehouse material handling systems , 2011 .

[21]  Safar Fazli,et al.  Separating successful and unsuccessful firms using multiple attribute decision-making methods , 2012, Int. J. Inf. Decis. Sci..

[22]  Henry Y. K. Lau,et al.  An agent-based dynamic routing strategy for automated material handling systems , 2008, Int. J. Comput. Integr. Manuf..

[23]  Dragan Komljenovic,et al.  Multi-attribute selection method for materials handling equipment , 2009 .

[24]  Sushil Kumar,et al.  Analytic hierarchy process: An overview of applications , 2006, Eur. J. Oper. Res..

[25]  T. Chu,et al.  A Fuzzy TOPSIS Method for Robot Selection , 2003 .

[26]  Cengiz Kahraman,et al.  An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application , 2010, Expert Syst. Appl..

[27]  Shankar Chakraborty,et al.  Selection of industrial robot using axiomatic design principles in fuzzy environment , 2015 .

[28]  Madjid Tavana,et al.  Supplier selection and order allocation with process performance index in supply chain management , 2012, Int. J. Inf. Decis. Sci..

[29]  R. Venkata Rao,et al.  Flexible manufacturing system selection using a combinatorial mathematics-based decision-making method , 2009 .

[30]  Rishi Kumar,et al.  Optimal selection of robots by using distance based approach method , 2010 .

[31]  B. M. Beamon,et al.  Performance, reliability, and performability of material handling systems , 1998 .

[32]  R. Venkata Rao,et al.  Rapid prototyping process selection using graph theory and matrix approach , 2007 .

[33]  Bijan Sarkar,et al.  Incremental analysis for the performance evaluation of material handling equipment: A holistic approach , 2013 .

[34]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[35]  R. Venkata Rao,et al.  Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods , 2013 .

[36]  Selin Soner Kara,et al.  Selecting the suitable material handling equipment in the presence of vagueness , 2009 .

[37]  S. K. Mukherjee,et al.  Integrating AHP with QFD for robot selection under requirement perspective , 2005 .

[38]  Fabio Polonara,et al.  A multi-criteria decision approach to choosing the optimal blanching–freezing system , 2004 .

[39]  M. Ilangkumaran,et al.  A hybrid MCDM approach for evaluating an automobile purchase model , 2013, Int. J. Inf. Decis. Sci..

[40]  Sasikumar Gnanasekaran,et al.  An integrated model for supplier selection: an automobile industry case study , 2010 .

[41]  İrfan Ertuğrul,et al.  Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection , 2008 .

[42]  Roger N. Wabalickis.  Justification of FMS with the analytic hierarchy process , 1988 .

[43]  Preetvanti Singh,et al.  Empowerment of women in India: a multi-criteria decision making approach , 2014, Int. J. Inf. Decis. Sci..

[44]  Ashraf Labib,et al.  A design strategy for reconfigurable manufacturing systems (RMSs) using analytical hierarchical process (AHP): A case study , 2003 .

[45]  Henry C. W. Lau,et al.  Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system , 2001 .

[46]  Osman Kulak,et al.  MULTI-ATTRIBUTE MATERIAL HANDLING EQUIPMENT SELECTION USING INFORMATION AXIOM , 2004 .

[47]  Kemal Vatansever.  Integrated Usage of Fuzzy Multi Criteria Decision Making Techniques for Machine Selection Problems and an Application , 2014 .

[48]  T. Saaty.  Axiomatic foundation of the analytic hierarchy process , 1986 .

[49]  A K Kochhar,et al.  An analytic hierarchy process approach to the choice of manufacturing plant layout , 1999 .

[50]  R. H. Sturges,et al.  Framework for the control of automated material-handling systems using the holonic manufacturing approach , 2004 .