An effective DFM strategy requires accurate process and IP pre-characterization

IEEE Des. Test. Comput.

2012

In the integrated circuit (IC) industry, all products must go through three phases before they are available in the market, namely design, manufacturing, and testing. Design, obviously, refers to the process of converting the early concepts of the product into a precise description of its implementation. Manufacturing then uses this description to fabricate the product, where the design is physically materialized onto the silicon wafer and later packaged into the product. If design and manufacturing are perfect, then every fabricated IC is completely functional, thereby obliterating the need for testing. Unfortunately, both design and manufacturing are not ideal; therefore every manufactured IC must be subject to stringent testing procedures to ensure that most bad ICs are identified and prevented from shipping to the end-users.ICs are deemed bad when they contain certain defects that cause the ICs to fail the specifications.Defects are unintended structural and/or material changes of the IC due to design/manufacturing imperfections.These physical changes may alter the electrical characteristics of the circuit, which are sometimes severe enough to lead to a failure (i.e., violation of one or more design specifications). Common defects in IC manufacturing can be caused by contaminations in the process, variations of the process conditions, or simply the difficulty to fabricate certain features of the design. The last issue is the focus of this dissertation. Defects that arise due to certain aspects of the design being sensitive to the manufacturing process with an elevated likelihood of failure are known as systematic defects. This dissertation addresses the issues related to the prevention and identification of systematic defects by analyzing a large amount of manufactured ICs that have failed testing.For systematic-defect prevention, one common approach is to use design-for-manufacturability (DFM) rules to communicate hard-to-manufacture features to designers so that these features can be minimized in the iii design. Obviously, different rules describe different features and thus their violation/adherence will have different impact on the manufacturability of the product. It is therefore desirable to measure the relative importance of the rules and how they affect product yield. To address this issue, a method called RADAR (Rule Assessment of Defect-Affected Regions) has been developed for measuring the effectiveness of DFM rules in preventing systematic defects. RADAR analyzes a large amount of test data of failed ICs to draw statistical conclusion.Taking preventive measures, such as enforcing DFM rules, is necessary to ensure sufficient product yield. Unfortunately, the amount of resource (circuit area, designer's time, etc.) dedicated to DFM can be quite limited. It is therefore impractical to anticipate and prevent every possible hard-to-manufacture design features before the product is manufactured. Thus, systematic defects can still exist. Therefore, a mechanism is required to identify systematic ...

Section: Dfm Rule Evaluationmentioning

confidence: 99%

Section: Dfmmentioning

confidence: 99%

Physically-Aware Analysis of Systematic Defects in Integrated Circuits

Tam¹,

IEEE Des. Test. Comput.

2012

“…Most approaches for evaluating DFM rules are employed prior to high-volume manufacturing [1][2][3]. Our methodology, termed here DREAMS (DFM Rule EvAluation using Manufactured Silicon), has the goal of measuring DFM rule effectiveness using information extracted from actual failed ICs.…”

Section: Introductionmentioning

confidence: 99%

DREAMS: DFM Rule EvAluation using Manufactured Silicon

2013 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

Wang

Xue

et al. 2013

DREAMS (DFM Rule EvAluation using Manufactured Silicon) is a comprehensive methodology for evaluating the yield-preserving capabilities of a set of DFM (design for manufacturability) rules using the results of logic diagnosis performed on failed ICs. DREAMS is an improvement over prior art in that the distribution of rule violations over the diagnosis candidates and the entire design are taken into account along with the nature of the failure (e.g., bridge versus open) to appropriately weight the rules. Silicon and simulation results demonstrate the efficacy of the DREAMS methodology. Specifically, virtual data is used to demonstrate that the DFM rule most responsible for failure can be reliably identified even in light of the ambiguity inherent to a nonideal diagnostic resolution, and a corresponding rule-violation distribution that is counter-intuitive. We also show that the combination of physically-aware diagnosis and the nature of the violated DFM rule can be used together to improve rule evaluation even further. Application of DREAMS to the diagnostic results from an in-production chip provides valuable insight in how specific DFM rules improve yield (or not) for a given design manufactured in particular facility. Finally, we also demonstrate that a significant artifact of DREAMS is a dramatic improvement in diagnostic resolution. This means that in addition to identifying the most ineffective DFM rule(s), validation of that outcome via physical failure analysis of failed chips can be eased due to the corresponding improvement in diagnostic resolution.

“…To perform DFM 1 , the designers must be aware of what to look out for, i.e., they need to know what systematic 2 issues can affect product yield. Semiconductor foundries provide DFM design rules [1][2] to aid designers in this aspect. The DFM rules are typically developed during process characterization or derived from experience learned from earlier technology nodes.…”

Section: Introductionmentioning

confidence: 99%

To DFM or not to DFM?

Tam

Proceedings of the 48th Design Automation Conference

2011

Design for manufacturability (DFM) is inevitable because of the formidable challenges encountered in nano-scale integrated circuit (IC) manufacturing. Unfortunately, it is difficult for designers to understand the cost-benefit tradeoff when tuning their design through DFM to achieve better manufacturability. This work attempts to assist the designer in this aspect by providing a methodology (called RADAR ---Rule Assessment of DefectAffected Regions) which uses failing-IC diagnosis results to systematically evaluate the effectiveness of DFM rules. RADAR is applied to the fail data from a 90nm Nvidia graphics processing unit (GPU) to demonstrate its viability. Specifically, evaluation of the via-enclosure rules revealed that they are much more needed in metal layers 3-6 than the remaining layers.