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All Journal SPEKTRUM INDUSTRI ComTech: Computer, Mathematics and Engineering Applications
Adi Permana
Universitas Mercu Buana
Computer Science & IT Engineering Industrial & Manufacturing Engineering Mathematics

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Journal : ComTech: Computer, Mathematics and Engineering Applications

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Design of Experiment (DOE) Analysis with Response Surface Method (RSM) to Optimize the Electroplating Parameter Adi Permana; Humiras Hardi Purba; Sawarni Hasibuan
ComTech: Computer, Mathematics and Engineering Applications Vol. 12 No. 2 (2021): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v12i2.6998

Abstract

Identifying optimum process parameters, their effects, and contributions to the outcomes of electroplating thickness in the electroplating process is very time-consuming and requires high cost. Small Medium Enterprises (SMEs) use a traditional approach in determining optimum process parameters that can lead to an inefficient result, such as a high variation in the response. Design of Experiment (DOE) can identify the significant factors in the process, show the correlation of each factor, and determine the optimum process parameter to achieve the targeted response (thickness). The research aimed to use DOE analysis with Response Surface Method (RSM) to optimize the electroplating parameter. It was experimental research using real production part as the DOE sample and Minitab statistic software to analyze the result. The used sample in the experiment was the continuous product order from a home appliance manufacturer. Then, four factors during the electroplating process were chosen: electrolyte concentration, electric current, duration of timing, and surface of the electroplated area. The results show that to reach thickness at 40 microns, it needs the optimum parameter with 5 minutes duration, electrolyte density of 22 Baume, electricity of 5 Volt, and surface area product of 415 cm2. This condition leads to capacity improvement of up to 100%. Hence, it decreases overtime costs and contributes to reducing energy consumption.
Co-Authors Edward Steven Humiras Hardi Purba Sawarni Hasibuan