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Wafer fabrication is a capital-intensive and highly complex manufacturing process. In a wafer fabrication facility (fab), wafers are grouped as a lot to go through repeated sequences of operations to build circuitry. Lot scheduling is an important task for manufacturers in order to improve production efficiency and satisfy customers' demands of on-time delivery. Cycle time and average work-in-process reduction while meeting customers' requirements play an important role in improving the competitiveness and sustainability of a semiconductor manufacturer. In this research, we propose the optimal combination rules for lot scheduling problems in wafer fabs, focusing on three complex areas of decision making: lot release control, batch sizing, and dispatching lots to enhance competitiveness and sustainability of a semiconductor facility.

Design of a system starts with functional requirements and expected contexts of use. Early design sketches create a topology of components that a designer expects can satisfy the requirements. The methodology described here enables a designer to test an early design qualitatively against qualitative versions of the requirements and environment. Components can be specified with qualitative relations of the output to inputs, and one can create similar qualitative models of requirements, contexts of use and the environment. No numeric parameter values need to be specified to test a design. Our qualitative approach (QRM) simulates the behavior of the design, producing an envisionment (graph of qualitative states) that represents all qualitatively distinct behaviors of the system in the context of use. In this paper, we show how the envisionment can be used to verify the reachability of required states, to identify implicit requirements that should be made explicit, and to provide guidance for detailed design. Furthermore, we illustrate the utility of qualitative simulation in the context of a topological design space exploration tool.

Abstract:The objective of this study is to seek better policy options for greenhouse gas (GHG) emission reduction in Korea's international aviation industry by analyzing economic efficiency and environmental effectiveness with a system dynamics (SD) model. Accordingly, we measured airlines sales and CO 2 emission reductions to evaluate economic efficiency and environmental effectiveness, respectively, for various policies. The results show that the average carbon emission reduction rates of four policies compared to the business-as-usual (BAU) scenario between 2015 and 2030 are 4.00% (Voluntary Agreement), 7.25% (Emission Trading System or ETS-30,000), 8.33% (Carbon Tax or CT-37,500), and 8.48% (Emission Charge System or EC-30,000). The average rate of decrease in airline sales compared to BAU for the ETS policy is 0.1% at 2030. Our results show that the ETS approach is the most efficient of all the analyzed CO 2 reduction policies in economic terms, while the EC approach is the best policy to reduce GHG emissions. This study provides a foundation for devising effective response measures pertaining to GHG reduction and supports decision making on carbon tax and carbon credit pricing.