When design rule is mitigating to smaller dimension, process variation requirement is tighter than ever and challenges the limits of device yield. Masks, lithography, etching and other processes have to meet very tight specifications in order to keep defect and CD within the margins of the process window. Conventionally, Inspection and metrology equipments are utilized to monitor and control wafer quality in-line. In high throughput optical inspection, nuisance and review-classification become a tedious labor intensive job in manufacturing. Certain high-resolution SEM images are taken to validate defects after optical inspection. These high resolution SEM images catch not only optical inspection highlighted point, also its surrounding patterns. However, this pattern information is not well utilized in conventional quality control method. Using this complementary design based pattern monitor not only monitors and analyzes the variation of patterns sensitivity but also reduce nuisance and highlight defective patterns or killer defects. After grouping in either single or multiple layers, systematic defects can be identified quickly in this flow. In this paper, we applied design based pattern monitor in different layers to monitor process variation impacts on all kinds of patterns. First, the contour of high resolutions SEM image is extracted and aligned to design with offset adjustment and fine alignment . Second, specified pattern rules can be applied on design clip area, the same size as SEM image, and form POI (pattern of interest) areas. Third, the discrepancy of contour and design measurement at different pattern types in measurement blocks. Fourth, defective patterns are reported by discrepancy detection criteria and pattern grouping . Meanwhile, reported pattern defects are ranked by number and severity by discrepancy. In this step, process sensitive high repeatable systematic defects can be identified quickly Through this design based process pattern monitor method, most of optical inspection nuisances can be filtered out at contour to design discrepancy measurement. Daily analysis results are stored at database as reference to compare with incoming data. Defective pattern library contains existing and known systematic defect patterns which help to catch and identify new pattern defects or process impacts. On the other hand, this defect pattern library provides extra valuable information for mask, pattern and defects verification, inspection care area generation, further OPC fix and process enhancement and investigation.