Multi-objective optimization of electrochemical discharge machining processes: a posteriori approach based on bird mating optimizer

In the modern manufacturing scenario, efforts are continuously being made to improve the performance of advanced machining processes. Electrochemical discharge machining (ECDM) is a hybrid non-traditional machining (NTM) process, which makes use of the combined advantages of two single-action NTM pr...

Full description

Saved in:
Bibliographic Details
Published in:Opsearch 2017-06, Vol.54 (2), p.306-335
Main Authors: Goswami, Debkalpa, Chakraborty, Shankar
Format: Article
Language:English
Subjects:
Application Article
Business and Management
Electrochemical machining
Machine tools
Machining
Management
Mathematics
Multiple objective analysis
Operations research
Operations Research/Decision Theory
Optimization
Performance enhancement
Process engineering
Process parameters
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the modern manufacturing scenario, efforts are continuously being made to improve the performance of advanced machining processes. Electrochemical discharge machining (ECDM) is a hybrid non-traditional machining (NTM) process, which makes use of the combined advantages of two single-action NTM processes, i.e. electrical discharge machining and electrochemical machining. As a result, the performance characteristics of ECDM process are considerably different from those of the two single-phase processes with respect to productivity, accuracy and surface quality. Selection of the optimal process parameters is always crucial towards fully utilizing the benefits of ECDM process. In this paper, an a posteriori approach based on the novel bird mating optimizer (BMO) is applied for multi-objective optimization of ECDM responses. In this approach, the complete spectrum of non-dominated Pareto optimal solutions, from which the process engineers can easily choose the desired parametric setting depending on the application domain, is developed. It is much more useful from a practical standpoint than a priori approaches reported in the literature. The BMO is also used to predict the overall trends of the multi-parameter dependent responses, without the need of holding any of the process parameters constant during analysis.
ISSN:0030-3887
0975-0320
DOI:10.1007/s12597-016-0285-2