EconPapers    
Economics at your fingertips  
 

Drilling Optimization via Particle Swarm Optimization

T. O. Ting and T. S. Lee
Additional contact information
T. O. Ting: Xi’an Jiaotong Liverpool University, China
T. S. Lee: Multimedia University, Malaysia

International Journal of Swarm Intelligence Research (IJSIR), 2012, vol. 3, issue 1, 43-54

Abstract: The drilling process based on Material Reduction Rate (MRR) is modeled in this work. The modeling of this process is rather time-consuming and expensive as it involves 32 experiments with appropriate apparatus. Having had the model, the authors employed the well-known algorithm, namely Particle Swarm Optimization (PSO) to solve the maximization problem with some constraints present. All the results obtained showed non-violation to the constraints imposed. It means the solutions found are all feasible. The developed program may be useful for some practical purposes such as estimating the drilling duration, proper time to change the drill etc.

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jsir.2012010103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:3:y:2012:i:1:p:43-54

Access Statistics for this article

International Journal of Swarm Intelligence Research (IJSIR) is currently edited by Yuhui Shi

More articles in International Journal of Swarm Intelligence Research (IJSIR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

 
Page updated 2025-03-19
Handle: RePEc:igg:jsir00:v:3:y:2012:i:1:p:43-54