INTEC   05402
INSTITUTO DE DESARROLLO TECNOLOGICO PARA LA INDUSTRIA QUIMICA
Unidad Ejecutora - UE
artículos
Título:
An improvement based MILP optimization approach to complex AWS scheduling
Autor/es:
A. AGUIRRE; C.A. MÉNDEZ; G. GUTIERREZ; C. DE PRADA
Revista:
COMPUTERS AND CHEMICAL ENGINEERING
Editorial:
PERGAMON-ELSEVIER SCIENCE LTD
Referencias:
Lugar: Amsterdam; Año: 2012 vol. 47 p. 217 - 226
ISSN:
0098-1354
Resumen:
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 limitedresources.Duetoitsinherentcomplexity,industrial-sizedautomatedwet-etchstationscheduling problems are rarely solved through full rigorous mathematicalformulations. 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 animprovementMILP-baseddecompositionstrategy that combines the benefits of a rigorous continuous-timeMILP (mixed integer linear programming)formulation with theflexibility 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