—This paper presents an optimization approach to
find optimal process parameters of multiple quality
characteristics in plastic injection molding (PIM). Melt
temperature, injection velocity, packing pressure, packing time,
and cooling time are selected as process parameters in the
experiment. Besides, product length and warpage are chosen as
multiple quality characteristics. Taguchi orthogonal array is
firstly conducted in the experiment and the experimental data
are employed to calculate the signal-to-noise (S/N) ratio.
Analysis of variance (ANOVA) is then used to find the best
combination of parameter settings for product length and
warpage. In addition, BPNN is used to construct an S/N ratio
predictor. Then, the S/N ratio predictor is associated with GA to
obtain the optimal process parameter. Finally, two
confirmation experiments are taken to exam the effectiveness of
proposed approach. Experimental results show that the
proposed optimization approach not only can satisfy the quality
characteristics, but also can improve process stability.
—ANOVA, BPNN, GA, injection molding,
Wen-Chin Chen and Shi-Bo Lin are with the Department of Industrial
Management, Chung-Hua University, No. 707, Sec. 2, Wu Fu Rd., Hsinchu,
Taiwan (e-mail: firstname.lastname@example.org, email@example.com).
Cite: Wen-Chin Chen and Shi-Bo Lin, "Process Parameters Optimization of Multiple Quality Characteristics in Plastic Injection Molding Using BPNN and GA," International Journal of Applied Physics and Mathematics vol. 3, no. 6, pp. 373-375, 2013.