dC Production

dC Production2017-09-18T23:17:34+00:00

Optimize and maintain yield

Making the yield ramp as steep as possible is the goal when introducing a new product. Being able to quickly optimize the device and process for manufacturability means a faster path to profitability.  For semiconductor test data analysis to efficiently and effectively pinpoint and correct yield inhibitors, you require a tool tailored for the task. Syntricity’s dC Production is an automated, highly interactive semiconductor yield management system that is accessed through a simple high-level dashboard.

Automated Semiconductor Test Data Analysis Flows

Automated analysis flows within dC Production provide the answers needed to accelerate yield ramp and gain early profitability. Automated test data flows collect, analyze and generate production reports that are accessed through Syntricity’s dC Production dashboard. A series of programmed “Stop Lights” and alerts displayed on the dashboard, focus attention on problem areas, while still maintaining access to all production information over a selected period of time. The ability to trace genealogy of material through all the operations, regardless of attribute name changes such as lot name or device is crucial. This enables material matching when correlating final test or wafer sort results to WAT results.

The dashboard also provides access to today’s single-lot reports and wafer map galleries, analyzed to highlight potential yield issues based on wafer spatial analysis. Users can view thousand of wafer maps in seconds or can focus only on the problematic few wafers for fast review and disposition.

dC Production Dashboard

Transform the way you make decisions

Syntricity’s dC Production Dashboard is designed to provide the industry’s best data visualization experience, supporting the unique way semiconductor engineers analyze data to assess problems and make decisions.

Through an intuitive, interactive experience, the dashboard enables users to visualize and analyze semiconductor test data. Smart decisions are made easy utilizing the dashboard’s three primary panels:  Yield Management, Test Floor and Foundry.

  • Yield Management Panel

    Users can navigate from the yield management panel to a summary view, which allows review of Operation and Step Yields on all devices processed for predefined time intervals. Selecting a device from the summary view drills down to individual device wafer sort or final test trends to identify yield issues and isolate problematic material within devices.

  • Test Floor Panel

    The test floor panel enables users to drill down and review site-level yield performance of all devices tested at different test facilities. Users can also identify particular hardware and software configurations used during test to isolate handler, site, prober, probe card or test program issues.

  • Foundry Panel

    As wafer maps are inserted into the dC Warehouse, they are analyzed to determine if any spatial yield patterns caused by known fabrication process problems exist. The wafers are then grouped into monitored categories for quick analysis and disposition. Users can view the entire wafer gallery or filtered galleries of wafers and drill-down to individual wafer detail views for review and links to other related information. Because dataConductor is able to store millions of wafer maps, users can create stacked wafer heat maps to assist them in identifying failure signatures, which can be used in creating control maps to avoid testing and/or identifying outlier material.

dC Production and dC Analysis Work Together

dC Production is integrated with dC Analysis, providing the user an efficient method for detailed, context-dependent analyses. dC Production provides automated analysis flows and the ability to trace the genealogy of material through all operations, providing such benefits as correlation of final test or wafer sort to WAT/PCM results. dC Analysis enables in-depth analysis at the serial measurement level for data characterization, engineering studies, and root-cause analysis of production parametric data.