Title : 
ACO-ICSA based scheduling of re-entrant manufacturing system with Mix-processing Style
         
        
            Author : 
Li Li ; Qingyun Yu
         
        
            Author_Institution : 
Coll. of Electr. & Inf. Eng., Tongji Univ., Shanghai, China
         
        
        
        
        
        
            Abstract : 
Semiconductor wafer fabrication facility (fab) is a typical re-entrant manufacturing system. It is characterized with reentrant process flows, mix processing models, large-scale and unbalanced production facilities. A hybrid method (ACO-ICSA), combining an ant colony optimization (ACO) with immune clone selection algorithm (ICSA), is proposed to solve its fab-wide scheduling problem. Its main idea is to find a scheduling solution for each bottleneck with batch or non-batch processing style by using an ACO or ICSA first, then re-unify these solutions to multiple scheduling plans for these bottlenecks satisfying precedence constraints, and finally obtain the scheduling plans of non-bottlenecks subject to those of bottlenecks and precedence constraints. These fab-wide scheduling plans are translated into the pheromone or affinity to guide artificial ants or antibodies to implement their new search processes. The Mini-fab model and an electrical equipment production line are used to verify and validate the proposed method. The simulation results show that ACO-ICSA improves the operational performance with better total weighted tardiness and makespan.
         
        
            Keywords : 
ant colony optimisation; artificial immune systems; manufacturing systems; production facilities; semiconductor industry; semiconductor technology; ACO-ICSA based scheduling; ant colony optimization; fab-wide scheduling problem; hybrid method; immune clone selection algorithm; mini-fab model; mix-processing style; re-entrant manufacturing system; semiconductor wafer fabrication facility; unbalanced production facilities; Batch production systems; Genetic algorithms; Job shop scheduling; Optimal scheduling; Processor scheduling;
         
        
        
        
            Conference_Titel : 
Automation Science and Engineering (CASE), 2014 IEEE International Conference on
         
        
            Conference_Location : 
Taipei
         
        
        
            DOI : 
10.1109/CoASE.2014.6899309