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.
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.
To solve the sequencing problem in mixed-model flexible assembly lines (MMFALs) with variable launching intervals, a mathematical model aiming to minimize the cost of utility and idle times is developed. To obtain high-quality sequences, an advanced scatter search (ASS) algorithm is proposed. A heuristic approach, i.e. launching intervals between products algorithm (LIBPA), is incorporated into the ASS algorithm to solve the launching interval problem for each sequence. Numerical experiments with different scales are conducted to compare the performance of ASS with genetic algorithm (GA). In addition, we compare the cost of variable launching intervals approach with fixed launching intervals approach. The results indicate that the ASS is efficient and effective, and considering variable launching intervals in mixed-model assembly lines (MMALs) sequencing problem can improve the performance of the line.
