Overhead-hoist-transporters (OHTs) have become the most appropriate tools to transport wafer lots between inter-bay and intra-bay in united layouts of automated material handling systems (AMHSs) in 300 mm semiconductor wafer fabrications. To obtain a conflict-free scheduling solution, an intelligent multi-agent-based control system framework was built to support the AMHSs. And corresponding algorithms and rules were proposed to implement cooperation among agents. On the basis of the mentioned above, a time-constraint-based heuristic scheduling algorithm was presented to support the routing decision agent in searching the conflict-free shortest path. In the construction of the algorithm, the conflicted intervals of the k-shortest-route were identified with the time window theory. The most available path was chosen with an objective of the minimum completion time. The back tracking method was combined to finish the routing scheduling. Finally, experiments of the proposed method were simulated. The results show that the multi-agent framework is suitable and the proposed scheduling algorithm is feasible and valid.
To quickly and accurately estimate the expected work-in-process (WIP)of material intersection points in continuous automated material handling systems (AMHSs) ,a queuing-based performance analytical model was presented for continuous flow transporters (CFTs) . In the modeling procedure which considered layout of crossovers and the variability of service time of turntables, an M /G /1 queuing model with multi-class customers and a non-preemptive priority M /G /1 queuing model with multi-class customers were introduced to accurately present the queuing WIP of each material intersection point and perform the analytical model. Finally,300 mm wafer fabrication facilities (fabs)with 24 bays were applied to evaluating the proposed model. Compared with results of an Arena simulation, the model performs well in evaluating the number of queuing WIP of the intersection points and overall system of CFTs in AMHSs.
In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling problems of parallel litho machines with reticle constraints,where multiple reticles are available for each reticle type.First,the scheduling problem domain of parallel litho machines is described with reticle constraints and mathematical programming formulations are put forward with the objective of minimizing total weighted completion time.Second,estimation of distribution algorithm is developed with a decoding scheme specially designed to deal with the reticle constraints.Third,an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally,simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.
With a comprehensive consideration of multiple product types,past-sequence-dependent(p-s-d) setup times,and deterioration effects constraints in processes of wafer fabrication systems,a novel scheduling model of multiple orders per job(MOJ)on identical parallel machines was developed and an immune genetic algorithm(IGA) was applied to solving the scheduling problem.A scheduling problem domain was described.A non-linear mathematical programming model was also set up with an objective function of minimizing total weighted earliness-tardiness penalties of the system.On the basis of the mathematical model,IGA was put forward.Based on the genetic algorithm(GA),the proposed algorithm(IGA) can generate feasible solutions and ensure the diversity of antibodies.In the process of immunization programming,to guarantee the algorithm's convergence performance,the modified rule of apparent tardiness cost with setups(ATCS) was presented.Finally,simulation experiments were designed,and the results indicated that the algorithm had good adaptability when the values of the constraints' characteristic parameters were changed and it verified the validity of the algorithm.
