Advances in Production Engineering & Management
Volume 9 | Number 1 | March 2014 | pp 21–30
http://dx.doi.org/10.14743/apem2014.1.173
Particle swarm optimization approach for modelling a turning process
Hrelja, M.; Klancnik, S.; Irgolic, T.; Paulic, M.; Jurkovic, Z.; Balic, J.; Brezocnik, M.
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A B S T R A C T
This paper proposes the modelling of a turning process using particle swarm
optimization (PSO). The independent input machining parameters for the
modelling were cutting speed, feed rate, and cutting depth. The input parameters
affected three dependent output parameters that were the main cutting
force, surface roughness, and tool life. The values of the independent and
dependent parameters were acquired by experimental work and served as
knowledge base for the PSO process. By utilizing the knowledge base and the
PSO approach, various models could be acquired for describing the cutting
process. In our case, three different polynomial models were obtained: models
a) for the main cutting force, b) for surface roughness, and c) for tool life.
All the models had exactly the same basic polynomial form which was chosen
similarly to that in the conventional regression analysis method. The PSO
approach was used for optimization of the polynomials' coefficients. Several
different randomly-selected data sets were used for the learning and testing
phases. The accuracies of the developed models were analysed. It was discovered
that the accuracies of the models for different learning and testing data
sets were very good, having almost the same deviations. The least deviation
was noted for the cutting force, whilst the most deviation, as expected was for
tool life. The obtained models could then be used for later optimization of the
turning process.
A R T I C L E I N F O
Keywords • Machining, CNC turning, Modelling, Optimization, Particle swarm optimization
Corresponding author • Hrelja, M.
Article history • Received 9 July 2013, Revised 26 November 2013, Accepted 15 January 2014
Published on-line • 12 March 2014
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