A decision guidance framework for non-traditional machining processes selection

Abstract In order to realize the manufacturing/machining demands thrived by newer, hard and difficult-to-machine materials being utilized in the present day industries, an assortment of non-traditional machining (NTM) processes has been developed over the past few decades. These processes are capable of generating intricate and complex shapes with high degree of accuracy, close dimensional tolerance and better surface finish. In this paper, a decision guidance framework is developed in Visual BASIC 6.0 to help the process engineers in selecting the most appropriate NTM process for a specific work material and shape feature combination. It also assists in identifying the ideal process parameter combinations for the most suitable NTM process. The derived results highly corroborate with the opinions of the experts in the related field, demonstrating the acceptability of the developed system.

[1]  Amitava Ray,et al.  Non-traditional machining process selection using integrated fuzzy AHP and QFD techniques: a customer perspective , 2014 .

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

[3]  Yusuf Tansel İç,et al.  An experimental design approach using TOPSIS method for the selection of computer-integrated manufacturing technologies , 2012 .

[4]  R. Venkata Rao,et al.  Optimization of modern machining processes using advanced optimization techniques: a review , 2014 .

[5]  Prasenjit Chatterjee,et al.  Nontraditional machining processes selection using evaluation of mixed data method , 2013, The International Journal of Advanced Manufacturing Technology.

[6]  Shankar Chakraborty,et al.  Applications of the MOORA method for decision making in manufacturing environment , 2011 .

[7]  Hakan Tozan,et al.  A fuzzy based decision model for nontraditional machining process selection , 2014 .

[8]  Miloš Madić,et al.  Selection of non-conventional machining processes using the OCRA method , 2015 .

[9]  Shankar Chakraborty,et al.  A decision-making model for non-traditional machining processes selection , 2014 .

[10]  H. El-Hofy Advanced Machining Processes: Nontraditional and Hybrid Machining Processes , 2005 .

[11]  Shankar Chakraborty,et al.  Non-traditional machining processes selection using data envelopment analysis (DEA) , 2011, Expert Syst. Appl..

[12]  Hakan Tozan,et al.  A fuzzy based decision support model for non-traditional machining process selection , 2013 .

[13]  Shankar Chakraborty,et al.  A combined TOPSIS-AHP-method-based approach for non-traditional machining processes selection , 2008 .

[14]  Shankar Chakraborty,et al.  A digraph-based expert system for non-traditional machining processes selection , 2009 .

[15]  Mustafa Yurdakul,et al.  Development of a multi-attribute selection procedure for non-traditional machining processes , 2003 .

[16]  Prasenjit Chatterjee,et al.  Advanced manufacturing systems selection using ORESTE method , 2013, Int. J. Adv. Oper. Manag..

[17]  Shankar Chakraborty,et al.  Application of PROMETHEE-GAIA method for non-traditional machining processes selection , 2012 .

[18]  Shankar Chakraborty,et al.  QFD-based expert system for non-traditional machining processes selection , 2007, Expert Syst. Appl..

[19]  Shankar Chakraborty,et al.  Design of an analytic-hierarchy-process-based expert system for non-traditional machining process selection , 2006 .

[20]  Bijoy Bhattacharyya,et al.  Development of an management information system as knowledge base model for machining process characterisation , 2007 .

[21]  R Jehadeesan,et al.  Web-based Knowledge Based System for Selection of Non-traditional Machining Processes , 2008 .