## 4 Simulation Experiments and Results
### Simulation Results and Analysis
#### 4.2.2 Analysis and Discussion  
1. Figures 14 and 15 show that a-HPDB outperforms HPDB and R-HPD in terms of ALDT for hot lots and normal lots, respectively. 2. Figure 14 shows that a-HPDB has the highest ALDT reduction for hot lots at the system configuration 2H96B (2% hot lot ratio and 96% bay loading). The advantages over HPDB and R-HPD are 7.64% and 16.32%, respectively. Figure 15 shows a-HPDB has the highest ALDT reduction for normal lots at the system configuration 10H98B. The advantages over HPDB and R-HPD are 10.38% and 22.85%, respectively. 3. Overall, for hot lots a-HPDB has a 4.14% and 14.89% fewer ALDTs than HPDB and R-HPD, respectively; for normal lots a-HPDB has an 8.92% and 18.52% fewer ALDTs than HPDB and R-HPD, respectively. 4. In addition, Figures 14 and 15 show that the higher the bay-loading ratio the higher the advantage for a-HPDB. For example, at the system configuration 10H92B, for hot lots the ALDTs obtained from a-HPDB, HPDB and R-HPD are 552.1 s, 568 s and 633.36 s, respectively, indicating that a-HPDB has a 2.8% edge over HPDB and a 12.83% edge over R-HPD. For normal lots, a-HPDB has an 8.74% edge over HPDB and a 15.27% edge over R-HPD. At the system configuration 10H96B, for hot lots a-HPDB has a 3.06% edge over HPDB and a 13.66% edge over R-HPD. For normal lots a-HPDB has a 9.1% edge over HPDB and an 18.8% edge over R-HPD. At the system configuration 10H98B, for hot lots a-HPDB has a 3.75% edge over HPDB and a 15.35% edge over R-HPD. For normal lots a-HPDB has a 10.38% edge over HPDB and a 22.85% edge over R-HPD. 5. Table 2 shows the AMHS efficiency obtained from a-HPDB, HPDB and R-HPD under different system configurations. It is found that the higher the bay loading the higher the efficiency for a-HPDB. This characteristic is especially important for a firm that faces increasing demands. 6. Note that the HPDB improved the R-HPD. In this research, the a-HPDB further improved the HPDB. The improvement mainly comes from the three additional dispatching rules (Rules 5, 6 and 7) used in the a-HPDB. Especially, rule 5 enables a wafer lot to direct change from Intra-Line 2 to Intra-Line 1. As a result, together with Rule 4, the a-HPDB allows a lot to change between two Intra-Lines to access an available machine. In contrast, the HPDB only allows a lot in Intra-Line 1 to access the available machines in Intra-Line 2. Nevertheless, we believe Rules 5, 6 and 7 all have contributions to the advantage of the a-HPDB method. 7. From the experimental results, we concluded that a-HPDB is the best one among the three methods as it can best deal with the \"traffic-jam\" problem while considering lot priority. To address the two problems, we have proposed a novel dispatching method, termed as a-HPDB, based on an AMHS restructured by ARB conveyor. Our simulation results showed that the a-HPDB outperformed two other methods, HPDB and R-HPD, proposed in previous studies. In terms of ALDT, for hot lots, a-HPDB is 4.14% better than HPDB and is 14.89% better than R-HPD; for normal lots, a-HPDB is 8.92% better than HPDB and 18.52% better than R-HPD. In addition, it is noted that the ALDT of normal lots is not much affected in case of higher bay-loading and hot-lot ratios. This characteristic is especially important for a fab facing increasing demand. Though we have demonstrated the advantages of restructuring AMHS using ARB, the use of ARB for the AHMS to be used in a 450 mm wafer fab should be prudent as both ARB and 450 mm wafer are new initiatives. More investigations and experiments are still required. For example, due to the increased weight and size, the 450 mm wafers will become more sensitive to vibration, thus more investigations are required to ensure the safety of wafers when transporting and handling these wafers. In addition, a thorough evaluation on the investment of ARB-based AMHS is also required. In future research, the development of more effective dispatching rules for the a-HPDB can be focused.