MULTI OBJECTIVE OPTIMIZATION OF TURNING OPERATION USING HYBRID DECISION MAKING ANALYSIS

Yıl 2017, Cilt: 18 Sayı: 3, 595 - 610, 30.09.2017

Mehmet Alper Sofuoğlu , R. Aykut Arapoğlu , Sezan Orak

https://doi.org/10.18038/aubtda.287801

Cited By: 6

Öz

In this article, surface
roughness, cutting forces and material removal rates of different materials are
examined in different cutting conditions in turning operations. First,
vibration characteristics (natural and chatter frequency, stiffness coefficient
and damping ratio) are determined by different cutting tests. Surface
roughness, material removal rate and cutting forces are measured during
experiments.  By using these experiments,
five different hybrid multi-criteria decision making models are proposed.
Cutting parameters are optimized by maximizing material removal rate and
minimizing surface roughness and cutting force. This study will enable the
operators and engineers to work more efficiently in the machining operations.   

Anahtar Kelimeler

Best-worst method, cutting force, MCDM

Kaynakça

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• [3] Puertas I. and Luis Perez C.J., Surface Roughness Prediction By Factorial Design of Experiments in Turning Processes, Journal of Materials Processing Technology, 2003;143 – 144: 390 – 396.
• [4] Jha N.K., A discrete data base multiple objective optimization of milling operation through geometric programming. Journal of Engineering for Industry, 1990;112: 368-374.
• [5] Wang Z.G., Rahman M., Wong and Sun J.,Optimization of multi-pass milling using parallel genetic algorithm and parallel genetic simulated annealing. International Journal of Machine Tools and Manufacture, 2005; 45(15):1726-1734.