Abstract

Metal cutting is a developing sector in the manufacturing industry, especially plasma cutting. Plasma cutting is a non-conventional metal cutting machining that use a high pressure plasma arc to melt the workpiece. The expected output of this cutting is kerf width as an indicator for quality of machining results and material removal rate (MRR) as an indicator for productivity of machining results, but in practice the results of the two outputs are contradictory. This plasma cutting technology is expected to not only be able to cut metal in bulk quickly but also to have quality cutting results that measured by the minimum kerf width results. Plasma cutting machining is affected by several parameters that can affect the two outputs generated, including current (I), cutting speed (Cs), stand of distance (Sod), and gas pressure (P), so we need a method to increase productivity and quality of machining results from plasma cutting machining results by finding the best combination of parameters that will result in high productivity and the best cutting quality. The Taguchi method is the most efficient optimization method that only requires less experiment but this method mostly finds interaction results between variables that cannot predict or find optimum results, so the response surface method (RSM) is chosen as a strategy to find the expected optimum value with a central composite design (CCD) approach. This study obtained two results of different optimum S/N ratio predictions where the design parameter flow is 60 A, cutting speed 1500 mm/min, standoff distance 1 mm, gas pressure 5 bar produces an optimum material removal rate of 19.662, and the current parameter design 60 A, cutting speed 1073 mm/min, standoff distance 3 mm, gas pressure 5 bar produces an optimum kerf width of 1,948. The optimal prediction results from both outputs after verification showed an increase in the response of 0.768 mm at the kerf width and 8.662 mm3/min at the material removal rate.

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