DSpace
 

DSpace at IIT Bombay >
IITB Publications >
Article >

Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/11586

Title: An evolutionary approach for multi-pass turning operations
Authors: SINGH, G
CHOUDHARY, AK
KARUNAKARAN, KP
TIWARI, MK
Keywords: genetic algorithm
machining operations
tool wear
optimization
constraints
design
Issue Date: 2006
Publisher: PROFESSIONAL ENGINEERING PUBLISHING LTD
Citation: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 220(2), 145-162
Abstract: Owing to the significant role that machining parameters play in performing successful and efficient machining operations, the determination of optimum machining parameters is a subject of high importance. The problems are well-known complex puzzles and are treated as a strongly non-deterministic polynomial (NP)-hard problem. In this research, a multi-pass turning problem has been modelled, taking into consideration several technological constraints pertaining to force, power, chip-tool interface temperature, tool life, stable cutting region, etc.; while aiming to satisfy the objective of minimizing the unit production cost. The solution of such a problem, even one of modest size, is marked by excessive computational complexity and therefore random search optimization techniques are needed in order to resolve the problem. In this paper, a heuristic has been developed to determine the number of passes and a new kind of genetic algorithm (GA), incorporating the features of chromosome differentiation and simulated annealing, has been developed and applied to address multi-pass turning problems. The proposed algorithm overcomes the drawbacks of simple GAs and the methodology adopted here has the capability of achieving a better balance between exploration and exploitation, and of escaping from local minima. The proposed algorithm has been tested on various case studies adopted from the literature, as well as on ten simulated data sets. Intensive computational experiments revealed its superiority over earlier approaches.
URI: http://dx.doi.org/10.1243/09544054JEM376
http://dspace.library.iitb.ac.in/xmlui/handle/10054/11586
http://hdl.handle.net/10054/11586
ISSN: 0954-4054
Appears in Collections:Article

Files in This Item:

There are no files associated with this item.

View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback