computational calculation for the optimal parameter settings using MATLAB, three confirmation experiments were conducted to assess the effectiveness of these methods.
According to the result from 25 product samples, the proposed system is the most stable performance for the length and warpage. The proposed optimization system is successfully found optimal parameter settings closer to the target length from 170.42 mm to 170.47 mm;
and reduces warpage from 0.198 mm to 0.096 mm. Moreover, the proposed system also smallest warpage value (0.096 mm), followed by the first stage (0.132 mm) and the Taguchi method (0.198 mm). Moreover, the process capability index (Cpk) value of the proposed system is the highest (4.05), followed by the first stage and the Taguchi method, 2.77 and 2.41, respectively. Even though the result of the first stage optimization is not as good as the proposed system, but this approach has better result than the Taguchi method.
The proposed optimization system is successfully found optimal parameter settings closer to the target length, with standard deviation from 0.0161 to 0.0138 (14.29%). In addition, the proposed system also successfully reduces standard deviation for warpage from 0.0462 to 0.0151 (67.32%).
Section 2 Future Work
Although this study successfully finds optimal parameter settings for plastic parts, future works need to be done in order to solve the problems in plastic injection molding.
The process parameters in this study are selected according to advice of experts in plastic injection molding, and other parameter settings are excluded from the consideration of the experiment. Therefore, in the future works, other control parameter settings such as mold temperature, injection time, velocity pressure switchover, etc., can be defined in the beginning of PIM process. Moreover, production cost estimation in plastic injection molding could be included within the next research. Another issue is the comparison of real experimental work and PIM simulation software. Computer aided engineering (CAE) software, such as Moldex3D and Moldflow are commonly used before conducting the real experiment. The optimization for parameter settings using CAE software is not investigated in this study, and this will be one of the motivating studies for future work.
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