OPTIMASI PROSES ELECTROPOLISHING PADA PEMBUATAN MULTILAYERED MICROFILTERS DENGAN PENDEKATAN FULL FACTORIAL DESIGN - , DAWI KAROMATI BAROROH, Andi Sudiarso, S.T., M.T., M.Sc., Ph.D. ([Yogyakarta] : Universitas Gadjah Mada, 2014)
Machining technology began to be applied in the field of biomaterials, one of them in the manufacture of multilayered microfilters for dialysis process. Making use of multilayered microfilters hard material and has a complex profile made by wet etching method. The methods produce toxic vapors and also involves hazardous chemicals that are not safe for both human health and the environment, so it appears the process of electropolishing (EP) as an alternative. EP process parameters it is necessary to have a lot of optimization to improve its quality and productivity, where the quality of the response in terms of the optimum value of material removal rate (MRR) and overcut. In this study analyzed the influence of voltage factors (level in 13, 15 and 17 volt) and feed rate (levels in 5.5, 6.5 and 7.5 mm/min), with replication as much as 3 times using a full factorial design approach. This study also uses dynamic machining with a copper electrode diameter of 4 mm and workpiece material in the form of stainless steel 204. The results obtained from this research that voltage factor, feed rate and the interaction of these two factors have a significant effect on the value of MRR and overcut value. The influence of each factor on the value of MRR and overcut formulated in the form of a linear regression model. In addition, to the highest MRR response obtained at a voltage of 17 volt and a feed rate of 7.5 mm/min with a value of 6.37 Ã 10-4 g/s, while for the lowest overcut response obtained at a voltage of 13 volt and a feed rate of 6 , 5 mm/min at 0.208 mm. The results of the analysis for both the response generated optimum conditions at a voltage 17 volt and a feed rate of 6.5 mm/min with MRR value of 5.533 x 10-4 g/s and overcut value of 0.351 mm. Keywords: Multilayered Microfilters, Eletropolishing, Material Removal Rate, Overcut, Full Factorial Design, Linear Regression Model