Producción CyT
Artículo
Autoría
Aguirre, Adrian Marcelo
;
MENDEZ, CARLOS ALBERTO
;
Gutierrez, Gloria Maribel
;
de Prada, Cesar
Fecha
2012
Editorial y Lugar de Edición
Elsevier
Revista
COMPUTERS AND CHEMICAL ENGINEERING,
vol. 47
(pp. 217-226)
Elsevier
Resumen
Información suministrada por el agente en
SIGEVA
The automated wet-etch station (AWS) is one of the most critical stages of a modern semiconductor manufacturing system (SMS), which has to simultaneously deal with many complex constraints and limited resources. Due to its inherent complexity, industrial-sized automated wet-etch station scheduling problems are rarely solved through full rigorous mathematical formulations. Decomposition techniques based on heuristic, meta-heuristics and simulation-based methods have been traditionally reported i...
The automated wet-etch station (AWS) is one of the most critical stages of a modern semiconductor manufacturing system (SMS), which has to simultaneously deal with many complex constraints and limited resources. Due to its inherent complexity, industrial-sized automated wet-etch station scheduling problems are rarely solved through full rigorous mathematical formulations. Decomposition techniques based on heuristic, meta-heuristics and simulation-based methods have been traditionally reported in literature to provide feasible solutions with reasonable CPU times. This work introduces an improvement MILP-based decomposition strategy that combines the benefits of a rigorous continuous-time MILP (mixed integer linear programming) formulation with the flexibility of heuristic procedures. The schedule generated provides enhanced solutions over time to challenging real-world automated wet etch station scheduling problems with moderate computational cost. This methodology was able to provide more than a 7% of improvement in comparison with the best results reported in literature for the most complex problem instances analyzed.
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Palabras Clave
Large-scale scheduling problemsMILP-based strategiesModeling and OptimizationHybrid decomposition approachWafer fabricationSemiconductor Manufacturing System (SMS)
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