A fuzzy multi attribute decision making approach for evaluating effectiveness of advanced manufacturing technology – in Indian context

Globalisation has increased opportunities for the manufacturers, as it has increased the customer size but at the same time it has brought competition. Customers are enjoying the variety of products at the minimum cost. Because of this, manufacturers are striving to improve their flexibility, quality of product, delivery time, etc. Manufacturers are adopting advanced manufacturing technologies (AMT), so as to meet these requirements. Adoption of (AMT) is a colossal investment and decision should be taken with proper evaluation. From the literature survey, it is proved that traditional financial methods for evaluating the effectiveness of AMT are not enough as it also enhances many intangible factors like flexibility, quality, employees' satisfaction etc. Therefore, in this paper an endeavour has been made to develop a model for the evaluation of AMT investments by using fuzzy graph theoretic approach (FGTA). FGTA quantifies the intangible factors and based upon these factors gives a single numerical index which is useful for managers to evaluate the effectiveness of AMT.

[1]  Sami Farooq,et al.  Risk calculations in the manufacturing technology selection process , 2009 .

[2]  Michael H. Small,et al.  Planning, justifying and installing advanced manufacturing technology: a managerial framework , 2007 .

[3]  Jack R. Mkrkdtth,et al.  Justification techniques for advanced manufacturing technologies , 1986 .

[4]  Zhengdong Huang,et al.  A Graph-Based Approach for Capturing the Capability Envelope of a Machining Process , 2003 .

[5]  Shian-Jong Chuu,et al.  Selecting the advanced manufacturing technology using fuzzy multiple attributes group decision making with multiple fuzzy information , 2009, Comput. Ind. Eng..

[6]  G. Anand,et al.  Development of analytic network process for the selection of material handling systems in the design of flexible manufacturing systems (FMS) , 2011 .

[7]  Werner Bruggeman,et al.  Investment Justification of Flexible Manufacturing Technologies: Inferences from Field Research , 1992 .

[8]  Aleda V. Roth,et al.  Optimal Acquisition of FMS Technology Subject to Technological Progress , 1991 .

[9]  Michael H. Small,et al.  Justifying investment in advanced manufacturing technology: a portfolio analysis , 2006, Ind. Manag. Data Syst..

[10]  Margaret F. Shipley,et al.  A fuzzy logic model for competitive assessment of airline service quality , 2009 .

[11]  G. Anand,et al.  Justification of world‐class maintenance systems using analytic hierarchy constant sum method , 2009 .

[12]  Angappa Gunasekaran,et al.  A framework of justification criteria for advanced manufacturing technology implementation in small and medium enterprises , 2006 .

[13]  V. P. Agrawal,et al.  Computer aided robot selection: the ‘multiple attribute decision making’ approach , 1991 .

[14]  Amiya K. Chakravarty,et al.  Strategic acquisition of new manufacturing technology: a review and research framework , 1992 .

[15]  Rosnah Mohd. Yusuff,et al.  Neural network application in predicting advanced manufacturing technology implementation performance , 2010, Neural Computing and Applications.

[16]  Sharon M. Ordoobadi.  Fuzzy logic and evaluation of advanced technologies , 2008, Ind. Manag. Data Syst..

[17]  Fahriye Uysal,et al.  Fuzzy TOPSIS‐based computerized maintenance management system selection , 2012 .

[18]  J. Meredith,et al.  Justifying new manufacturing systems: a managerial approach , 1990 .

[19]  Victor B. Kreng,et al.  Strategic justification of advanced manufacturing technology using an extended AHP model , 2011 .

[20]  O. P. Gandhi,et al.  Digraph and matrix methods for the machinability evaluation of work materials , 2002 .

[21]  M. H. Small,et al.  Investment justification of advanced manufacturing technology: An empirical analysis , 1995 .

[22]  S. G. Deshmukh,et al.  A decision support system for selection and justification of advanced manufacturing technologies , 1997 .

[23]  D. Northcott,et al.  Strategic Investment Appraisal , 2007 .

[24]  Mohsen Attaran,et al.  The automated factory: Justification and implementation , 1989 .

[25]  V. Grover,et al.  An assessment of survey research in POM: from constructs to theory , 1998 .

[26]  V. P. Agrawal,et al.  A digraph approach to TQM evaluation of an industry , 2004 .

[27]  Jianping Dou,et al.  Graph theory-based approach to optimize single-product flow-line configurations of RMS , 2009 .

[28]  Om Prakash Yadav,et al.  A fuzzy-AHP-based framework for prioritising benchmarks in the service sector , 2010 .

[29]  Sandeep Grover,et al.  Role of human factors in TQM: a graph theoretic approach , 2006 .

[30]  Sharon M. Ordoobadi.  Evaluation of advanced manufacturing technologies using Taguchi's loss functions , 2009 .

[31]  O. P. Gandhi,et al.  Failure Cause Analysis—A Structural Approach , 1996 .

[32]  David Dugdale,et al.  Evaluating Investments in Advanced Manufacturing Technology: A Fuzzy Set Theory Approach , 2001 .

[33]  John R. Baldwin,et al.  Impediments to advanced technology adoption for Canadian manufacturers , 2001 .

[34]  M. H. Small,et al.  Advanced manufacturing technology: Implementation policy and performance , 1997 .

[35]  Peter G. Burcher,et al.  Competitiveness strategies and AMT investment decisions , 2000 .

[36]  Vincent F. Yu,et al.  An integrated fuzzy multi-criteria approach for the performance evaluation of multiple manufacturing plants , 2010, Comput. Ind. Eng..

[37]  K. Vizayakumar,et al.  Fuzzy hierarchical decision making (FHDM): a methodology for technology choice , 2014 .

[38]  M. R. Abdi,et al.  Fuzzy multi-criteria decision model for evaluating reconfigurable machines , 2009 .

[39]  R. P. Mohanty,et al.  Advanced manufacturing technology selection:A strategic model for learning and evaluation , 1998 .

[40]  Loghman Hatami-Shirkouhi,et al.  Evaluating and prioritising critical success factors of TQM implementation based on fuzzy AHP , 2012 .

[41]  Abby Ghobadian,et al.  Strategic investment appraisal for advanced manufacturing technology , 2014 .

[42]  Azhar Ahmad,et al.  Relationships between Investments in Advanced Manufacturing Technology (AMT) and performances: Some empirical evidences , 2008 .

[43]  R. Venkata Rao,et al.  Selection, identification and comparison of industrial robots using digraph and matrix methods , 2006 .

[44]  G. Anand,et al.  Selection of lean manufacturing systems using the PROMETHEE , 2008 .

[45]  F. Lefley,et al.  Manufacturing investments in the Czech Republic:: An international comparison , 2004 .

[46]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[47]  Godwin J. Udo,et al.  Advanced manufacturing technologies: Determinants of implementation success , 1996 .

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

[49]  M. F. Wani,et al.  Development of maintainability index for mechanical systems , 1999 .

[50]  V. P. Agrawal,et al.  Quality modelling and analysis of electroplating system using graph theory matrix approach , 2011 .

[51]  C. McDermott,et al.  Organizational culture and advanced manufacturing technology implementation , 1999 .