However, there are many articles investigating the simu- lation of the plastic injection molding which are influenced by the process parameters on the  quality  problems.  One of the most significant of these articles is successfully applied by Chen et al. (Ref 13). This article  deals  with  the application of computer-aided engineering integrating with statistical  technique  to  reduce  the  warpage  based  on     the

plastic injection parameters. For this purpose, a number of Moldflow analyses dependent on the Taguchi orthogonal arrays, the regression equations, and analysis of variance (ANOVA) have been coupled to predict the  warpage  at various injection parameters. But, this article only summa- rizes the results of the warpage without  those  of  the shrinkage during the plastic injection molding. Nevertheless, another article performed by Chen et al. (Ref  14) has employed for analysis and modeling of effective  parameters on the shrinkage variation of injection molded part by exploiting a number of Moldflow    analyses.

In contrast to the mentioned investigations, a different study was executed by Altan (Ref 15) to reduce the shrinkage in injection molding using Taguchi method, ANOVA, and Neural network. Twenty-seven injection molding experiments were performed to obtain the shrinkage values for two different polymer materials of Polypropylene (PP) and Polystyrene (PS). From this study, it can be seen that an integrated approach is presented to obtain minimum shrinkage corresponding to the best process conditions. As different from the literature above, some researchers only focused on the machining processes which are the Electric Discharge Machining (EDM) (Ref 16, 17). In summary, even though these researchers work the different fields, they have employed the similar methods as well as the plastic injection molding.

In this study, an effective regression model based on FE analyses obtained from Moldflow simulations was created to model the mathematical relationship between the plastic injection process parameters (the mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage using ABS polymer material. Most of the studies in the literature have not considered to all these process parameters. The ranges of the process parameters also differ from the studies in the literature. ANOVA analysis was performed to identify the most signif- icant process parameters and to evaluate the adequacy of the regression model for the shrinkage of the plastic injection molding. Additionally, the experiments for four plastic injection moldings of the plastic part of a DVD-ROM cover were carried out to compare the shrinkage results of the simulated values

Table 1 The levels of plastic injection moulding process parameters

No Process parameters Units Levels

1 Mold temperature Tmold, °C 40-60-80

2 Melt temperature Tmelt, °C 230-240-250

3 Injection pressure Pinj, Mpa 80-100-120

4 Injection time Itime, s 1-2-3

5 Cooling time Ctime, s 10-15-20

Table 2    Shrinkage results obtained from FE   analyses

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