Design of Experiment (DOE) Analysis with Response Surface Method (RSM) to Optimize the Electroplating Parameter

Authors

  • Adi Permana Universitas Mercu Buana
  • Humiras Hardi Purba Universitas Mercu Buana
  • Sawarni Hasibuan Universitas Mercu Buana

DOI:

https://doi.org/10.21512/comtech.v12i2.6998

Keywords:

Design of Experiment (DOE), Response Surface Method (RSM), electroplating parameter

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.

Dimensions

Plum Analytics

Author Biographies

Adi Permana, Universitas Mercu Buana

Master of Industrial Engineering Program, Industrial Engineering Department

Humiras Hardi Purba, Universitas Mercu Buana

Master of Industrial Engineering Program, Industrial Engineering Department

Sawarni Hasibuan, Universitas Mercu Buana

Master of Industrial Engineering Program, Industrial Engineering Department

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Published

2021-11-09

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