MULTI-OBJECTIVE OPTIMIZATION OF PLASMA ARC CUTTING PROCESS USING MOORA COMBINED WITH GA

Document Type : Original Article

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Faculty of Engineering, Menoufia University, Shebin Elkom, Egypt

Abstract

In this work, cutting parameters were optimized in plasma arc cutting process of mild steel by application of
multi-objective optimization by ratio analysis (MOORA) method. Standard deviation (SDV) concept has been
used to allocate the weight criteria of each objective being reflected. Cutting speed, arc current, and standoff
distance were nominated as setting parameters for optimization the kerf characteristics in the straight-slit
cutting (kerf taper, dross, surface roughness and maximization of material removal rate). MOORA was used to
transform multiple responses into a single characteristic index known as multi performance characteristic index
(MPCI). MPCI was modeled by the use of genetic algorithm (GA). With this action an attempt was made to
find more precise dependence of MPCI with cutting parameters. Finally, this was followed by optimization of
the MPCI in plasma arc cutting using genetic algorithm. This has also been that, SDV-MOORA-GA method
has effectively optimized the plasma arc cutting process parameters used in this study.

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