The manufacturing process of semiconductors is highly intricate, with each step requiring equipment, materials, and maintaining process parameters. Scheduling plays a role in semiconductor manufacturing. Currently, the focus of scheduling in this industry revolves around production-related performance indicators (KPIs) like cycle time, throughput, and yield. However, not much attention has been given to energy consumption and emission reduction during the scheduling process. It is worth noting that semiconductor manufacturing is an energy-intensive procedure that contributes to greenhouse gas emissions. Consequently, there is mounting pressure on companies to minimize their impact. This thesis concentrates on addressing the challenges faced during the photoresist coating step within the photolithography process by optimizing scheduling to reduce carbon footprint. To achieve this objective effectively a Multi Mixed Integer Linear Programming (MO MILP) model has been developed. This model facilitates trade-off analysis, between optimizing emissions and reducing makespan during changeovers. Ultimately it empowers decision makers to make choices that align with sustainability goals while maintaining production efficiency.
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The manufacturing process of semiconductors is highly intricate, with each step requiring equipment, materials, and maintaining process parameters. Scheduling plays a role in semiconductor manufacturing. Currently, the focus of scheduling in this industry revolves around production-related performance indicators (KPIs) like cycle time, throughput, and yield. However, not much attention has been given to energy consumption and emission reduction during the scheduling process. It is worth noting t...
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