## 3 Results and Discussion
### Results of the Taguchi Method and ANOVA  
Table 5 exhibits the simulated data of the maximum mean temperature and temperature uniformity in each group of experiments and their respective S/N ratios. Figure 4 shows the main effects plots for means and S/N ratios of three factors. The factors' magnitude of influence is determined by the difference between the maximum and minimum S/N ratios: the larger the difference, the greater the influence. As presented in Figure 4a, the temperature uniformity was most affected by heating depth and then by current and frequency successively. It first rose and then declined as the heating depth extended. It first decreased and then increased with rising frequency. It reduces as the current increases. At this level of factors, the optimal temperature uniformity was achieved at a heating depth of 7 mm, a current of 800 A, and a frequency of 20 KHz. Figure 4b illustrates the extent to which the three parameters affect the maximum mean temperature. It can be found that this temperature rises with the decrease of heating depth and the increase of current and frequency. In other words, the maximum mean temperature is negatively correlated with heating depth but is positively correlated with current and frequency. In respect to this temperature, the optimal combination of these parameters is as follows: the heating depth is 5 mm; the current is 1200 A; and the frequency is 40 KHz. Table 6 describes the ANOVA of each factor based on the 95% confidence interval (CI), which is used to evaluate how much each factor influences the maximum mean temperature and temperature uniformity. In this analysis, the P value of less than 0.05 means the factor is an important one affecting the target results [23]. It is observed from Table 6 that the maximum mean temperature is most affected by current, with a contribution rate of 95.54%, which is followed by heating depth with a contribution rate of 4.17%, while frequency has little impact on this temperature, showing a contribution rate of 0.29%. Therefore, the influence extent of current is much higher than that of the other two factors. By contrast, the heating depth is the most important factor affecting the temperature uniformity, showing a contribution rate of 59.59%. It is followed by the current with a contribution rate of 40.18% and then by the frequency with a contribution rate of 0.23%. Among them, heating depth and current are principal factors influencing the temperature uniformity, while the impact of frequency is negligible. To sum up, the target values are significantly affected by heating depth and current, with their influence extents much higher than that of the frequency. The percentage for the contribution rates of different factors is presented in Figure 5.  
Figure 2: Temperature rise curve under different parameters: (**a**) depth, (**b**) current, (**c**) frequency. Figure 3: Temperature distribution nephograms on the mold surface under different parameters. Figure 4: Main effects plots in the Taguchi experiment: (**a**) main effects plot for S/N ratios of three factors in respect of temperature uniformity; (**b**) main effects plot for S/N ratios of three factors in respect of max. mean temperature; (**c**) main effects plot for means of three factors in respect of temperature uniformity; (**d**) main effects plot for means of three factors in respect of max. mean temperature. Figure 5: Percentage for the contribution rates of different factors: (**a**) contribution of each parameter to the max. mean temperature; (**b**) contribution of each parameter to temperature uniformity.