For process development of deep-subwavelength technologies, it has become accepted practice to use model-based simulation to predict systematic and parametric failures. Increasingly, these techniques are being used by designers to ensure layout manufacturability, as an alternative to, or complement to, restrictive design rules. The benefit of modelbased simulation tools in the design environment is that manufacturability problems are addressed in a design-aware way by making appropriate trade-offs, e.g., between overall chip density and manufacturing cost and yield.The paper shows how library elements and the full ASIC design flow benefit from eliminating hot spots and improving design robustness early in the design cycle. It demonstrates a path to yield optimization and first time right designs implemented in leading edge technologies. The approach described herein identifies those areas in the design that could benefit from being fixed early, leading to design updates and avoiding later design churn by careful selection of design sensitivities. This paper shows how to achieve this goal by using simulation tools incorporating various models from sparse to rigorously physical, pattern detection and pattern matching, checking and validating failure thresholds.The time when design rule (DR) correct layouts could be processed in the manufacturing lines with no or minimal post tape out intervention is long past. Many advanced techniques have been developed to improve the lithographic entitlement. Their success allowed for the design to concentrate on producing best manufacturable "target" design in the hope that the manufacturing can reproduce it on wafer, but things became more complicated as the critical dimension shrank further. To control the risk of systematic failure the tendency is to make the design rules more complex, but this in itself does not guarantee pattern fidelity. With fewer companies manufacturing integrated circuitry and with increasing technology complexity, designers have become more interested in using all the information available to improve design manufacturability. This and the well understood increased difficulty of capturing design intent leads to increased motivation for manufacturing, technology development, and design teams to collaborate to create high yield parts creating a "must fix" contract. Design and process co-optimization becomes the norm. This process encompasses the tool and tuning capability to determine critical constructs, identifying those with the worst performance, and the guidance to resolve those manufacturability issues. A margin for adverse variation is also accounted for within the performance consideration.The goal of this paper is to show that a consistent framework provides a mechanism to detect and rank manufacturability problems in design, while guiding the correction process. A predefined set of guidelines is needed to understand what degree of process knowledge is sufficient for building a useful DfM tool.