An approximate analytical method for the performance evaluation of semiconductor front-end fabrication with model-based inspection and rework policies in process control

Semiconductor front-end fabrication involves a highly complex and flexible job shop environment, prompting extensive research into modeling system performance and supporting efficient adaptive decision-making. Considerable attention has been directed toward photolithography, as it is considered the most critical processing step, with inspection processes directly influencing both the defect detection capability and overall productivity. Typically, to ensure precision, each wafer layer undergoes thorough inspection with measurement markers spread across the entire wafer surface, resulting in long inspection times. Recent studies have shown that model-based process control coupled with the optimal down-selection of measurement markers can significantly enhance system performance. Building on this insight, this study aims to expand the analysis of semiconductor front-end fabrication by proposing a novel analytical model for the evaluation of the steady-state performance of quality and productivity. The model accounts for the material flow split based on quality attributes: defective parts are either scrapped or sent to rework stations, whereas undetected defects continue through the line. In addition, it integrates the dynamics of the full front-end process chain, offers a comprehensive representation of the system, and supports informed inspection policy decisions. This model has been effectively used to optimize inspection strategies, enabling a balanced trade-off between quality control and system productivity. Furthermore, the approach is generalizable and applicable to other manufacturing contexts that face similar trade-offs between inspection effort, resulting quality levels and throughput.